A rree is a set of points with which is associated a structure, that is to say a relation having the properties:

The relation between two points is directed (one

point depends on the other)

A point Cannot depend on a point belonging to its

own descent set (the descent set of a point is the

set of points that depend on it, the points that

depend on them, etc. )

A unique point descends from no other. It is possible to draw a tree placing below a point all of its descendants, linked by lines. (See the example on the next frame. ) A labeled tree is a tree such that with each of its points is associated a lab-el This label IS formed of a set of data. The figure below represents a labeled tree. fernthe,-nom commurr feminin, sin&ul.ier irresisxible adjectif, fcr-ir,iri singu*ier derivation negative du verbe resister vers I adjemlf jeur~e adjectif, feminin singulier rousse adjectif,couleur f5minin,singulier. une, article indef ini, f eminin singulier 7: T-E ATEF SYSTEM The purpose of the ATEF system is to transform an input sming of words into a labeled tree, each word in the string possibly,leading to one or several points in the final tree (ambiguity). The determination of the label originating in an input word results from its analysis. This analysis proceeds by segme~tation of the input word according to elements from different dictional: ies . A correct segmentation therefore gives. a label for a point of the final tree . Tn advance of any. analysis, the definition of the elements employed in the composition of different labels is required and is supplied by two Eiles called variable declaration files. A label will consist of a set bf variables. Each variable must be defined with its set of possible values. Thus if one defines the variable "category" the set of "categories" that can be used must be specified. The set is written category = (NOUN, ARTICLE, PRONOUN, ADJECTIVE, VERB, ...) (A constraint requires that the name of a variable must not be longer than 7 characters. Thus the preceding var2able could be written, for example, CAT = (NN, ART, Pm, ADJ, VRB, ...) )

The definitdon of a particular label consists in an enumeration of the variables relevant to the label. A set of labels can be predefined and is collected in a so-called format file. The ATEF system analyzes the words and thus employs dictionaries A dictionary is a set of segments (character strings), ~ t each h of which is associated a label, a processing pointer, and a lexical unit pointer. The processing pointer specifies the particular process which must be associated with the segment.

The analysis of the input word by the ATEF system resides at first in a label processing, that is to say in an evolution of the empty label toward a final label characteristic of the

analyzed word This evolution is controlled by the grammar, which at each moment has access to two labels. the label being

developed (noted by the symbol C) and the label associated w i th

the segment which was read in the dictionary (noted by A) The analysis of a word aims to produce a segmentation of the woru simultaneously compatible with the segments of the different dictionaries (the word must be an assembly of dictionary segments) and compatible with a correct evolution of the grammar Thus the segmentation of the input ~o rd is tighcly bound to the evolution of the grammar which controls the coherence of the segmentation In the course of a segmentation operation the state of the system takes into account for the analyzed word the label resuLting from the analysis of the segments al~eady obtarned for this word the label associated with the segment found in a dictlonary the remaining characters of the input word the complete form of the input word Thus for example in the course of the analysis of the word irresistible and after analysis of the segment "ible" and in the course of reading the segment 'resist1' the following erements are obtained C A The character$ IR the label resulting from the analysis of "ible" This label contains for example the variable derivation with value verb-adj, the variable gender with value masculine and feminine, the variable number with value singular. the label associated with the segment''resist This label coatains notably the lexical unit "resister", the varlable category with value verb The complete form IRRESISTIBLE The purpose of the grammar is to permit or prevent the evolution of label C starting wlth label A Here, the label will evolve and obtaln the variable category wlth value adjective. A rule associated with the segment "resist" by means of its pointer will therefore describe this evolution of the label C. When no evolution of the label C is possible, the corresponding segmentation is blocked and considered nonsignificant. The set of labels plays a fundamental role in this system and forms the set of sts~tes o f the finite state transducer corresponding to the logical model of the system Each coherent segmentation of a word (a word can have several coherent segmentations leading to ambiguities) provides a labeled point in the final tree Three elements are fundamental to the system the choice and evolution of the segmentation the calculation of the set of labels associated with a word the positioning of the labeled points created by the analysis of a word in the final tree The choice and evolution of the segmentation has to do with the sequence of input characters. The segmentation forces, above all, a prior linguistic choice. Thus with the segment "UN" two possibilities can be conceived either accept "UN E" as a coherent segmentation or have the segment "Ul?E" in the dictionary and refuse the segmentation "UN El' For each initial form several segmentations are possible to arrive at the same results arid only a linguie tic study of the phenomena permits a decision on the strategy to be adopted. In any event, this stLategy is left to the user of the system In the course of a segmentation the system can operate d~rectly on the nonsegmented chatacters in order to force them into a "canonical'! form. Thus in the case of the word reel several possib~lities arise to accept a word like realite put the segment "real" in a dictionary as well as the segmenf "reel", the former will generate words like realite, irrealite, etc. put the single segment "reel" in the dictionary and the analysis of the word realite Qill follow the schema

realit& => 1st segment found "lte", remainder "real"

mddificat&on real ->r&el => 2nd segment found "reel"

segmentation ."riSel it&" N B In thls analysis, it is to be noted that the search for successive segqents is performed from left to right £ox the input word. This depends on the strategy adopted and, for a given use, the direction of the segmentatson of a word can be either left to right or right to left.

To avoid a proliferation of possible segmentations and therefore of possible solutions, several functions provide for intervention in the segmentation A first possibility is offered b:~ the management of the dictionaries In fact, the system includes several dictionaries and after isolation of each segment the system can I I open" or "close" a dictionary This method makes it easy to avoid, for example, looking €or two consecutive prefixes. Another mode of intervention uhich is more direct, is peovided by the presence of functions acting on the enumeration procedures by which the system counts ~ f solutions. f For example, the system analyzes all possible segmentations starting with a given segment beginning with the segmentations containing most characters. An intervention at this level makes it possible hot to analyze but to reject subsegmentations of P segment. The analysis of the segment "UNE" can, for example, reject the analysis of the subsegment "UN E" (Observe that the segmentation of the word "chacune" will then be obtained as GAC UNE because th8 segmentation CHACUN E will. be rejected as a subsegmentation of "UNE" This problem can easily be resolved because these functions appear in the rules of the grammar and are consequently conditional. One can at the same time f"orbid the subsegmentation "UN E-" in the word "UNE" and aur;horize this. segmentatian in the word "CHACUNE")

The calculation of the set of labels associated ~ith aword is produced and controled by the grammar. This calculation corresponds above all with a conditianal modification of the label C or current state starting from the label A or argument state. The condition for the evolution of this label is such that if no evolution is possible then the corresponding segmentation Ls rejected. This condition can refer to the labels of the preceding analyzed words and can condition its result on the analysis of the following form. Thus for example in the course of the analysis of the word "LA" in the sequence "il la voit", the segmentation taking "la" as article can be rejected. The transfer of information to different labels can be realized through assignmenttothe following label S. When this label has been assigned in the course of the analysis of a word the analysis of the follow'ing word w i l l begin with the assigned label instead ef the null label. The final result of the system is a labeled tree. With no supplementary specification in the course of analysis, this tree appears in the following form: Au A w n .p - -- >* I solution & phrase p phrase p (~hrase) consists of a string A 0' w ---- fi, 43 solution I 1 phrase ph~ase I

The solution for a sentence of labels (one for each word of the sentence), each of which represents an interpretation of a ward of this sentence. In this case, the sentence is not structured; simply the ambiguities are sepa~ated. Th the course of the analysis of the words, a first sketch of a construct5an can be made and give as result a more developed tree. These functions specify the position that the point to which the calculated mask applies must take in the final tree. This position is determined in all cases below a point w, and is relative to the root (first point on the left below wi) and to the rightmost point of the tree already constructed. Thus this point can become itself the root, the rightmost leaf, etc. With, for example, the analysis of the string "une belle maison", we can. have during the analysis of 11 une", no tree during the analysis of "belle", the tree eontains the single point "une". A function can render the point "belle" as root and give belle une during the analysis of "maison", if the constructed tree is belle,. a function can provide for swapping we the root with the occurrence in work and give the tree une belle. In this case, the result for the system w i l l be une belle 5 , THE CETA SYSTEM The CETA system provides for writing and s5mulating a transformational grammar. This system manipulates labeled trees of the type described above (labeled trees produced by the ATEF or other system). To construct a transformational grammar with this system two complementary elements are necessary: the set of rules used defines the set of prfmitives of the system for a given application The set of grammars and the definition of their linkage defines the mode of use of the primitives

The definition of a transformation rule defines a mode of potential transformation of the tree considered. A rule is defined by a le'fthand part representing the subtree to be modif ied and a righthand part defining the resulting subtree. For example, let the following be two rules: ART NMC ART [UM~ ART NMC NMC ART On the tree resulting from the analysis by the ATEF system of the senterice "une irresistible jeune femme rousse", we w i l l have the following applications: une art. i r rgs ls t ib le jeurre femme rousse irresistible .ibunz GT*' rousse edj. adj. adj. adj. - NVC e ! , adj. A a d j . art. [JMC i uns irresistible jeune femme 'ousse art. ! adj. ad I j .. @ I . NMC wj . irr6sistible Jeune femme rousse adj. a g adj. I 1 8 une art. I

In fact, the~defin'itton of a transformation can call on a hierarchical set of subtrees. In the example taken here, the input tree is not very "deep" and most often only one-level trees are applicable. However, in the course of development of a cornplete structure, tshe considered tree is arbitrary and the definition of a complex transformation constructed beginning with several subtrees is very refined. The subtrees defined in a rule can likewise be considered. ordered or unordered Let rule R3 below be considered as unardered: -T ADJ NIVIC . NMC 1 Several apprications of this rule are possible on the same in-put as befme. une irrOsistible jeune femme rousse art. i NMC a b # W une irrgsiStible femme rousse aft. b une irresistible jeune femme rousse adj. : . adj. NMC : at une jeune art. i aGj. I NMC --. I a I jeune adj. . femme rouisu NMC . .. - aqj. I uns ~1 -~ -~~1 s~ jeune ib l e f~mme rousse art. adj. NMC adj. I I - f aQJ. uric' irrisistible jeune femme* art. adj. aqj. NMC I % I I rousse adj.

The linkage of the different rules previously described is defined by the set of elementary grammars. An elementary grammar c~~n~ists of ordered rules. A rule Ri will be applied prior to an R. if the order of R. is less ahan the order of R 1 j An J elementary grammar has furthermore a mode of execution. Atl elementary grammmar unitarily executable is such that its result will be obtained after an application of a part of the set of rules mentioned. (An application of the rules mentioned can cause to appear new possible applications which will not be performed in this case.) Anoth-er mode of application of an elementary grammar is exhaustive. In this mode, the set of rules of the gzammar will be applied up ro the maximum but the application of a given rule has the effect o f eliminating it from this elementary grammar. (That is, for a given point.) With this second mode of application, the number of possible steps for a given tree is always finite. Within an elementary grammar which is unitarily or exhaustively exechtable, the presence of recursive rules makes. it possible to obtain complex constructions by simulating repetitive procedures. A recursive rule is charaoterized by a call to a new grammar (which can obviously be the same as thae in which the recursive rule is found). The result of'the application of a recursive rule consists of the tree obtained after transformation by the called grammar of rhe tree transformed by the rule in question. For example, let R3 and R2 be the-rules previously described. The elementary grammar G consistiag of these two rules will furnish as result, In unitary mode: application of R3. (Priority is given by the order of enumeration of the rules.) une irrgsistible jeune femme rousse art. adj. I adj. NMC adj'. I a a I . a une irrgsistible femme rousse art. adj. NMC .... aGj. . a I In exhaustive mode: application of R3 then R2. (figure at top of next frame) une irresistible jeune fe&ne rousse adJ. adj. \ t rdMC i une irrgsistible femme rousse art. aqj. ? I NMC a . . jeune I adj. une jeune

adj . With Grammar G' containing rules R3 and R2, but specifying that R3 LI~US~ be recursive and call G', we have: W .JnG irr6sistPble jeune femme rousse une irr6sistible femme rpusse art. arjj. adj. NMC adj adj. ; I 4 # I f I une f mnie rousse irreiistible jeune ad9 .. adj, -.-- A une f ernme a~t. - NMC III adj. adj. art. agj. I femme adj . adj. 3dj @ a, 1. Application of rule R3* corresponds to the1 recursive call of this rule, terminating when the rule is nb longer applicable. With rules R4, R5, and R6, the construction is ART GN I ADJ GN l A ADJ GN'I art. add. sdj. NMC adj. une GNI irresistible adj. GiVl f smme NMC

The definition of a CETA grammar consT-s-t-s of a set of elementary grammars and a conditional linking procedure over them. The linking must he such that the Corresponding graph is loop-free. An elementary gxamar from which no linking is possible yields as result the input tree in place of the transformed tree. This procedure permits one to obtain a methad of analysis involving several criteria of acceptance, each consisting in the presence of a tree schema in the terminal tree. REFERENCES Chauche, J. P. Guillaume, and M. Quezel-Ambrunaz. Le systeme A.T.E.F. Internal document, G.E.T.A. December 1972. Chauche, J. Arborescence et transformation. Thesis, Grenoble. December 19.74 Chauche, J. Presentation du systeme C.E.T.A. Internal document , C..E.T.A. January 1975. Translation of a tcx~ prepared for the First National Gonference on Computational Linguistics, Varna, May, 1975. American Journal af Computational Ling?listics CONC E P TU A L A N A L Y S I S INVENTORY AND ANALYSIS OF TERMINOLOGY IN POLITICAL SCI ENCE Box 1830, Station B , Varlderbil t University Nashville , Tennessee 37235

At the 1970 International Political Science Associatio~ Congress in Munich, the first informal meeting was held of what became Research Cornittee Number One of the Association, the Committee on Conceptual and Tem~nological Analysis (COCTA) This committee (which includes political scient ists, sociologists, anthropologists, linguists, and philosophers) has been moving toward several objectives of concept clarification in political and social analysis. COCTA has organized panels at many polirical science and socialogy associations, including its formal, association with the C mparative Interdisciplinary Studies Section of the International Studies Association as the Internet on Conceptual and Terminological Analysis. Over the half-decade of its existence, COCTA has developed sever31 separate stages of concepmal analysis including special foci on metalinguistics, concept construction and reconstruction, and clarification of the theoretical usages of concepts. Underlying these and other interebts is a prerequisite need for an inventory of concepts-in-use. The rationale for attempting to develop the inventory, and discussion of its potential usages, are fully stated in my Commencement of a Systematic Concept COCTA Cozlection This statement sets forth the description of the resulting official COCTA Concept inventory2. The inventory is a rather ambitious project that will depend upon the contributions of interested scholars. It will begin with special focal points within political science and sociology as a pilot project. The logic of this pilot collection, however, is to provide a framework within which che collection can be expanded into other social sciences and related fields in the humanities. The immediate task is to commence the collection of social science concepts-in-use and to demonstrate the inventory's utility. Since the inventory can be commenced only by volunteers, the aid of scholars from several disciplines is essential to its success. Any concepts can be listed by interested scholars.

The present proceduxes for entering concepts into the inventory are simple. Scholars in the fields record concepts and related information according to the inventory's format and mail them .tro me. These materials will be edited and sent to Carl Beck at the University of Pittsburgh where the concepts and information will be recorded and stored (the Pittsburgh

'~ittsburgh: Univer.sity Center for International Studies, No. 9, 1974. See also the other COCTA papers listed therein.

2~he fha l design of the collection has seriously benefitted from comments from Fred W Riggs, from those who attended a special workshop on the inventory at the 1975 International. Studies Association Meeting in Washington (including Carl Beck, James B j orkman, Judy Bertelsen, Ray Corsado , David Hays, Ray Johnston, R. J. KirkbrPde, David Nasatir, Stephenie Neuman, Jona than Pool, Char les Powell, Fred Riggs , Henry Teurie, Theodore Bukahara, and Alan Zuckerman), and special responses from David Hays and Glenda Patrick. COCTA 43 system also houses, among other important resources, the United States Political Science Information S~S~~~--UPSIS)~ Except for the labor and postage costs, to be absorbed by scholars one way or another, Beck's technical and storage assistance permits commencing the inventory without funds. Once the inventory is seriously commenced, funds should quickly follow. INVENTORY FORMAT For each definition of a concept from the literature, the following information should be recorded by typing the information on- 8% x 11 inch paper. The identification of field and its contents should follow as below, with the information replacing the field descriptions. The information for some fields may either not be available or not be relevant, but NO RECORD WILL BE STORED THAT DOES NOT COMPLETE THE INFORMATION F8R THE FIRST. SEC~D , AND THIRD FIELDS. Each definition of a concept will be assigned an entry number when placed in the inventory because of multiple definitions for a specific term, but this will not affect the records sent from the field. FIELD 1 2 DESCRIPTION OF CONTENTS THE TERM USED BY THE AUTHQR TO REFERENCE A CONCEPT, e.g

consensus' (IE the term is not English, it shauld be followed by a coma and the closest English translation ORIGINAL LANGUAGE DEFINITION DIRECTLY FROM THE TEXT. If the term and definition are in a language other than English, the definition should be followed by an EXACT

3~he UPSIS is a special abstracting and retrieval system of political science articles, books, papers, etc., published in the United States which are indexed and retrieved by using the American Political Science Association's Political science Thesaurus, eds. Carl Beck, Eleanor D. Dym, and 3. Thomas McKechnie (Washington, D.C.: American Political Science Association, 1975). COCTA 44 English translation. (Because exact translation may require familiarity with the article, these entries require exceptional care.) 3 The source of the definition should be fully cited by AUTHOR, TITLE OF PUBLICATION (article and journal title if appropriate), PUBLICATION INFORMATION (full standard references for book, journal, or other paper or publication), and PAGE(S) from which the DEFINITION is drawn If guidance for full citations is needed, the most complete reference is A Manual of Style, (12th ed. ; Chicago and London: University of Chicago Press, 1969) 4 RELATED CONCEPTS should be noted by identifying terms associated with the meaning identified by the definition. The use of a term is, of course, arbitrary since rneaningful associations must be with other concepts, but the associations of terms w i l l provide guidelines specified by the individual recording the entry. Each related concept (identified by terms) listed should be preceded by BC, NC, RC, or OC as follows: BC BROADER CONCEPT of which the recorded concept is a

less extensive definition

NARROWER COWCEPT of which the recorded concept is a

more extensive definition

RELATED CONCEPT of which the recorded concept is on

the same LEVEL of extension, though different in extension

OVERUAPPING CONCEPT of which the recorded concept

shares extension Category of concepts as either THEORETICAL or OPERATIONAL INDICATOR should be noted simply by entering either '!theoreticalw or "operational" in this field. This w i l l NC RC OC 5 6 facilitate searches for sets of measures far concepts in devising research designs. ENGLISH LANGUAGE DESCRIPTIONS OF THE USE O 'F THE CQNCEPT should be recorded. For example., "Revolution is defined only for use when analyzing third world nations from the COCTA 45 perspective of demographic measures. " These descriptions should attempt LO characterize the type and level of theory employed as completely as is possible. Several sentences can be used. Retrieved definitions then CAN be limited to only those concepts which ALSO have description terms of interest in this file For example: REVOLUTION/THIRD WORL,D/DEMOGRAPHIC. (Since the collection will be stored in the same retrieval network as USPSIS, the APS Thesaurus terms provide useful guides for types of descriptors that can be used in both systems .)

3. an ANALYZER of English, due to Riesbeck a SEMANTIC MEMORY Component, due to Rieger a GENERATOR OF ENGLISH, due to Goldman The aim of Schank's system is to provide a representation of meaning in terms of which different kinds of analysis and machine translation can be carried out; a representation, moreover, that is independent 0.f any particular language ,. and of syntax, and, indeed, of all traces o f surface structure

After a detailed description of Schank's so-called CONCEPTUALIZATIONS, built up by conceptual categories, primitive acts, cases, etc., Wi-lks gave his own comments an Schank's system.

Like that of Schank, Wilks's system has a uniform representation, in the shape of structures and primitives, for the content of natural language. It is uniform in that the TUTORIAL ON COMPUTATIONAL SEMANTICS 52 information that might conventionally be considered syntactic, semantic or factual is all represented within a single structure of complex entities (called FORMULAS and PARAPLATES), all of which are in turn constructed from 80 primitive semantic entities. The formulas are tree structures of semantic primitives, stored in the dictionary of the system. The main element in any formula is its "head", i. e. the fundamental category to which the formula belongs. Sentences and their parts are represented by the socalled TEMPLATE STRUCTURES, built up as networks of formulas. Templates always consist of an agent node, an action node, and an object node, and other nodes that may be governed by these. A formula or, say, the noun."drinkl' can be thought of as an entity at a template action node, selecting a liquid object, that is to say a formula with FLOW STUFF as its head, to be put at the object node of the template (sentence structure). This seeking is preferential in that formulas not satisfying a given requirement will be accepted, but only if nothing satsifying it can be found. The template ultimately established for a fragment of text is the one in which the most formulas have their preferences satisfied. This preference principle is of essential importance in connection with solving the many ambiguity problems in natural language texts. When the local. inferences have been done that set up the agentr action-object templates for fragments of input text, the system attempts to tie these templates together so as to provide an overall initial structure for the inaut called a CASE TIE. TUTORIAL ON CUMPUTATIONAL SEMANTICS 53 Case ties are made with the aid of angther class of ordered structures called PARAPLATES, each of which is a string of functions that seek inside templates for information. The last step in the parsing is the inference procedure in which commonsense inference rules attempt by a simple strategy to construct the shortest possible chain of rule-linked template forms, on the principle of preference. The other main section of this course was a comparison of the parsing systeps described, including Charniak's system. This,comparison was based on the following principal aspects:

LEVEL OF REPRESENTATION. At this point there qre two Opposite views: that language can be realized or represented at different levels depending on the subject matter, or that the appropriate level of computation for inferences about natural language has to be to some degree reduced. The different level attitude is supported mainly by Colby and Charniak, while Schank and Wilks hold that a certain primitivization is necessary

CENTRANTY OF INFORMATION. This aspect concerns the degree of specificity of the information required. Some systems, Iike Charniak's, are based on infomation highly specific to particular situations, while the sorts of information central to Sohank's and Wilks's systems are of a much niore general nature, consisting mainly expectations, and great theoretecal example: A person of partial assertions about hman wants, so on. This problep of centrality is of importance, which Wflks illustrated by an

might know nothing of a particular type of TUTORIAL ON COMPUTATIONAL SEMANTICS 54 situation, for instance a birthday party, but could not for this reason be accused of not understanding the language. Yet, if he did not have available some very general inference such as for instance people gettihg sleepy at night, then it is possible that his failure to understand quite srmple sentences would cause observers to think that he did not know the language. Wilks went on: An interesting and difficult question that then arises is whether those who concentrate on and less central areas of discourse could, weld their bodies of inference together in as to create a wider system; whether, to put another way, natural language is a whole that can be built up fr~m parts. PHENOMENOLOGICAL LEVEL. This is a question of degree of explicitness. Here Schank s system is distinctive. Wilks's opinion is that the amount of detailed inference that a system may perform must be llmited not to go beyond 'commpn sense'.. As an example he mentioned Schank's analysis of the action of eating (performed by moving the hands to the mcuth) and described it as Ugoing too far from the 1 meaning' of eating, whatever that may be, towards generally true information about the act which, if always inferred about all acts a£ eating, will carry the system unmanageably far. . . . There clearly is a danger of taking inferences to a phenomenological level beyond that of common sense," he concluded. central in principle, such a way

the matter TUTORIAL ON COMPUTATIONAL SEMANTICS 55 DEGOUPLING. The issue is whether the actual parsing of text fnto an understanding system is essential.. Charniak and Minskr believe that this initial parsing can be decoupled. In Wilks's opinion this is not so, because he belkeves semantic analysis to be fundamental and because many of the later inferences would actually have to be done already, in order to have achieved the initial parsing. Also the problem of systematic ambiguity may be met much more efficiently with a system that does not decouple the parsing from rhe inference procedure.

AVAILABILITY OF SURFACE STRUCTURE. In first and second generation systems it is generally accepted that word-sense is closely a. associated with the surface structure of the sentence, but Schank has made a point of the-nonavailability of the surface structure, on the grounds that an ideal representation should be totally independent of the input surface structnre and words. In connection with this claim of Schank's, Wilks pointed out two things: in many cases the order of the sentences in.a text is part of its surface structure, and this information should be available in some way. The other point conceined the form of =epresentation employed Wilks was not sure that a structure of primitlves. is sufficient for specifying and distinguishing word senses adequateLy without transferring information specifically associated with the input word.

APPLICATION. This concerned the way in which different systems display, in the structures they manipulate, the actual procedures of application-of those structures to input text or TUTORIAL ON COMPUTATIONAL SEMANTICS dialogue Here the most distinctive. system is that of Wfnograd where the procedural notation, by its nature, tends to make clear the way in which the structures are applied. In hi6 view, as stated in some of his more recent writings, the control structure of an understanding program is itself of theoretical significance, for only with a control structure, he believes, can natural language programs of great size and complexity remain perspicuous. FORWARD INFERENCE. IS it neaessary to make massive forward inferences as one goes Schank do, or can one adopt understanding and generate system is unable to solve, superficial methods? Charniak's argument is that, unless forward inferences are made during the analysis, the system will not in general be able to solve ambiguity or reference problems that arise later. Wilks had some theoretical difficulties. tn arguing against this view, and he admitted the difficulty of defining a degree of forward inference that aids the solution of later semantic problems without going in t~ unnecessary depth

THE JUSTIFICATION OF SYSTEMS. Finally Wilks tried to contrast. the different modes of justification implicitly appealed to in terms of the power of the inferential system employed, of the provision and"formalizatfon, of a system's actual performance, and of the linguistic or psychological. plausibility of the proffered system of representation.

through a text., as Charniak and

some laziness hypothesis' about

deeper inferences only qhen the say, a referential problem by more TUTORIAL ON COMPUTATIONAL SEMANTICS 57 In his conclusion Wilks concentrated on those areas where the greatest problems within the field of A1 are found. The following needs seem to be the most pressing ones the need for a good memory model (stressed by Schank), the need for an extended procedural theory of texts and for a more sophisticated theory of reasons, causes, arid motives for use in a theory of understanding. Wilks ended his survey by stressing the fact that there is an AI paradigm of language understanding which embraces first and second generation approaches and goes back to a considerable amount of earlier work in computational linguistics INFERENCE AND KNOWLEDGE - Eugene Charniak

Why do we make inferences? We do when we use language and when we decode the information conveyed by language, i . e. in the case of structural disambiguation as well as in word-sense disambiguation, reference determination, question answering, translation, smarizfng, etc., everywhere a thing not stated explicitly has to be assumed. In so doing we are looking Eor a piece of information, for knowledge beyond the given text or situation Charniak poses five questions about how knowledge is used to make inferences: 1 What concepts, and in what combinations, do we need to record our impressions of the wgrld? (semantic representation) 2. Under what circurnstanees and why do we make inferences? (inference tr ipgering) TUTORIAL ON COMPUTATIONAL SEMANTICS 58 3. 4. How do we 1ocate.the needed information? (organization) 1, Once located, how do we know how to vSe the information? (inference mechahism) 5. @hat is the knowledge that we have of the world that enables us to understand language? (content) After this program had been put forth, Charniak presented ~ww partial answers to the questions the first order predicate calculus (FOPC) and the programing language PLANNER. FOPC consists of a+ language for expressing facts and rules for deriving new facts from old. The language consists of constants, variables, predicates, functions, logical connectives, and quantifiers. There are rules for inference. Charniak then outlined RESOLUTION THEOREM PROVING. It is a system for setting up proofs for deciding which rule of inference to use. Charniak proceeded to look at the five questions he had set forth and examined what answers. FOPC provides to them. He concluded that FOPC is primarily a theory ot inference mechanism,, but that it says very little about semantic representation. As FOPC dogs not tell how one is to locate the facts which are to be used to prove the derived result, theoretically we come up against a huge amount af possibilities when we combine the number of possible clauses.with the number of possible resolutions. This is called the "combinatorial explosion'" and is a serious problem in most inference systems, not only far FOPC.

Charniak then examined the ~roblern of when we make inferences. There are two obvious occasions when we may make one: TUTORIAL ON COMPUTATIONAL SEMANTICS 1. When a question is asked which requires an inference to be made (question time) 2. When the system has been given edough input i-nformation to make the inference (read time) Although the inference making restricted to question time would seem to be more - ,economical since inference.is -_ done only - - when we _- - -. . -- - - -< - must, in oraer to answer the system user's question', there is some ovide~ca that inference is done at reading t ime (e .g . psych~logical experiments on recall of texts). Furthermore, it is not possible to do word sense or steuctural disambiguation. withovt making inferenc-es. Wilks makes a distincti~n between 'broblem occasioned" and "nonproblem occasioned" inference. A typical example of the latter is given in -"Janet shook ner piggy-bank. There was no sound.. " We assurnel that there is nothing In the piggy-bank although the problem has not yet arisen in the story. Charniak believes that to do question answering on complex stories the system must perform nonproblem occasioned inference. ne glves examples rrom children's stories where persons lie about things and where the system has to.guess why the person is lying

An alternative to FOPC is to use the natural properties of some programming language to make inferences. Bertram Raphael (1968) did this .ih the system SIR when he used LISP to construce a data base. Another way is making the programing languagesmore suited to the needs of inference making. Such a system has t&rl designed but not implemented: PLANNER TUTORIAL ON COMPUTATIONAL SEMANTICS 60 (Hewi'tt 1969) In this system we are able to pick up an assertion by knowing parts of it If no appropriate assertion can be made, we can try to have theorems (i.e. programs) investigated An antecedent theorem is one where we are given the antecedent and'we assert the consequent, while w i th a consequent theorem we are asked to p-row the coasequen-t and we try to find the antecedent. PLANNER has the ability to choose which theorems to use on the basis of their patterns. This is called PATTERN DIRECTED INVOCATION. Furthermore, the system can back up to see if any earlier choices night be changed. This feature is somewhat controversial, since it might encourage the construcLi0n of programs which depend on blind search. PLANNER'S advantage over FOPC is that it offers several built-in organizational features, tne primary one being pattern directed invocation. A disadvantage about it as theory of knowledge and inference is thar: it is too vague Charniak (197.2-) illustrates the pros and cons of PLANNER using children's stories. Given a piece of simple narration, the system should be able to answer reasonable quegtions about it. Charniak Stresses the need for looking ahead in thg story to make inferences For this he uses. an anteceden~ theorem or a "demon". The routines which are available to set up demons he calls ensE ROUTINES. In addition- he makes use BOOKKEEPING for updating the assertions and of Consequent theorems pealled FACTFI-NDERS: the basic idea behind faetfinders is that they are used to establish facts whieh-are'not too important so that we do not want to TUTORIAL ON COMPUTATIONAL .SEMANTICS nssert thew and store them in the data base.. The main advantage of this system is that it provides a good theory of srganization. It states in particular that "given a particular assertion. the way we find those facts which we should use to nake inferences from the assertion is to 'look in two & places-. first the base routine for assertions of that form, second for any demons.which happen to have been activated which are looking for assertions of that ford"' Charniak concluded his lectures by examining the recent works of three scholars:

1. McDermott ' s system TOPLE (1.974) is rnalnly concerned with the problem of 'beliefs, describing a simple world consisting of a monkey and an experimenter in a single room. The program listens to a present-tense account of what is happening in the zoom; it tries to understand why things happen and what can be sxpected to happen as the story poas on. It tells us at t.he end of every sentence what new assertions it has assumed as a rbesult of hearing. TOPLE's restrictions are the following: it does not answer questibns, it does not handle actual natural language but rather a formal-looking input language. On the otrrer hand, it tries to visualize concretely a situation. It is based on a "multiple wo.rld structure"

2. Rieger (1974) is the first to have attempted to use Schank's conceptual dependency theory within a theory af inference and knowledge. Rieger!~ program has as its main purpose tc make reasonable inferences from the input it is given. The TUTORIAL ON COMPUTATIONAL SEMANTICS 62 input is expressed in a suitable formalism, i.e. conceptual dependency representation. It is also designed to understand stories, engage in dialogues, figure out references and wordsense ambiguity, answer questions about the way the world normally is 3. Minsky ' s (1974) frames are reinterpreted by Charniak as "a collect-ion or questions to be asked about a hypothetical situation. Frames specify issues to be raised and methods to be used in dealing with them. I t

Charniak also gave a double lecturn on SYNTAX IN LINGUISTICS. This was an introduction to generative grammar for those who had not had a. formal course in linguistics. MEMORY MODELS - Greg W- Scraqg.

After introducing SEMANTIC NETS, Scragg discussed their most important properties and compared several systems indluding some with partial semantic nets, some with partially quantitied semantic nets, some with fully quantified semanttc nets, and some with executable semantic nets.

He compared semantic net representations and predicate calculus tepresentations.

Attempts to construct proofs in the predicate calculus will show the difficulty CXE sklecting the relevant infqrrnation for making a particular deduction from a specif-ic fact. The techniques currently employed in theborem proving programs are even less efficient,a.t selecting the most relevant material. TUTORIAL ON COMPUTATIONAL SEMANTICS In comparison 3f predicate calculu-s and semantic nets, most problems center around the question of quantification. How does one quantify relations in a semantic net? Scragg mentions three different approaches. 1. There are six possible quan~~ficatio~s fur a two-place predicate Pxy vxv yPxy , ZxVyPxy , 3yVxPxy, Vz3yPxy, *VyIIxPxy, 3?$3yPxy In Scragg (1973) the claim is made that #the first three forms are so rare in everyaay (nonscientif?~) s-ituations that they may be ignored. The rematning ones may be distinguished with a type-token flag.

2. palme (1973) tries to represent quantification by introducing a third quantifier, ITS (meanins spme-thing like the possessive pronoun "its"). With three quantifiers, he now cam define six separate relations for each pwvious relation: Quantifying with FOR-ALL or EXISTS on the Left and FOR-ALL., EXISTS, or ITS on the r-ight of the old relation. One disadvantage of this is that he potentially has six times as many relations to work with and has to keep erack of the relationships between each of the six versions of the same-relation.

3. Schubert- (1975) treats quantifiers in a different way. He first puts the predicate calculus representation of the statement into SKOLEM FORM (a form which has no existential quantifiers and with all- universal quantlfiers outside 05 the body of the express-ion), Any node that is existentially TUTORItAL ON COMPUTATIONAL SEMANTICS 64 quantified but dependent an a universally quantified node is connected to that governing node. An event is asserred if and only if there is no arrow pointing to that node in the diagram. The ~---~~"--""--------"----"""""i.iiiiii"iiiiiiiii" semantic net structures here tend to become very complex. .., a"". - . .. ." .... .- . -1 - I - - . . - ---- . . . . . d l " .----.. .L It is not clear that any of the three approaches give really practical (or int~~tively satisfying) results. What we need at present is a theory of more conplex actions. For example, how do we link the descriptions of the various substeps of the pro.cess of cake making into a single desciiption of the overall action of making a cake?

There arb those who claim that all knowledge is stored in the form of procedures and there are those who clraim that it is stored as a collection of facts.

Scragg (1974; see also Nonuan 1973 and Norman et a1 1975) takes an intermediate approach by making use of ambiguous (data or procedure) representat-ions to store information about actions. The system knows how to simulate various human actions-such as toasting bread, making spaghetti sr cleaning up the kitchen. The information ab~ut how to perform these siinulatibns is: stored as procedures. However, these procedures can be used as data by other parts of the system to answer such questicms. as "'HOW do you make a ham and cheese sandwtich?"., "How many utensils do you use if you make a mushroom omelette?" or "Why did Don use a knife?" TUTORIAL ON COMPUTATIONAL SEMANTICS SEMANT I CS I'N LI NGU I ST I CS SEMANTIC MARKERS AND SELECTIONAL RESTRICTIONS. Phillip Hayes discussed in detail the influential paper by Katz and Fodor (1963). He concluded that their semantic theory is n0.t qufte adeouate even for the purely linguistic system they try to outline. everth he less, it can be a useful component of an A1 theory of natural language comprehension. GENERAT~IVE SEMANTICS. Margaret King outlined the defining characteristics.of this theory and then concentrated on its relationship with AI. As a conclusion, she stated that the definition of grammar logically should be extended to embrace not only wellformedness and semantic acceptability but also all possible aspects of the context of use of a sentence. This is contradictory to the traditional view of grammar-understood aF the sole means of determin'ing which sentences are grammatical for the majority of speakers of the standard form oE the language.

CASE GRAMMAR. Wolfgang Samlowski snrv-eyed- Fillmore's theory with special reference to Its -intLuence on American linguistic theories of semantics and on leading researchers within AI. The survey consisted of a presentation of case grammar, an examinatlon of some explicit and implicit traces lett in A1 by the Case grammar theory, and a demonstration of some of the complications that the acceptqnnre of the case gradrmar theory by language-understanding researchers would. cause TUTURIAL ON COMPUTATIONAL SEMANTICS DIVERSE PHILOSOPHY of= LANGUAGE. Yorick Wilks, in a double lecture, compared and contrasted modern philosophy with relation to linguistics, in particular systems of formal logic, represented by the works of Ludwig Wittgenstein and Richard Montague. The survey had special reference to the application of such systems of formal logic to the preparation of language understanalng system-s.

PSYCHOLOGY OF LANGUAGE AND MEMORY.: Walter Bischof gave a selective historical survey of the prevailing concepts in the field: association, organization a£ data, Gestalt, meaningfulness of data, temporal structure of memory, reaction-time paradigm to investigate semantic memory and the network models of representation as proposed by C.ol'15ns and Quillian (1969) Recent work based on the same assumption has shown that the structure of semantic memory is not quite the logical, bier.archical and economical structure proposed by Collins and Quillian. Bischof gave a list of possible relationships between artificial intelligence and cognitive psychology and concluded that these two disciplines have Little to say to each other because of their different aims and because the available experimental tools proposed by psychology are too poor.

LISP. Margaret King taught an "0-level" course and Philip Hayes a more advanced introductory course, to this programming language, which is being used widely by AT researchers, in its original form or in some of its extensions (CONNIVER, PLANNER). TUTORIAL ON COMPUTATIONAL SEMANTICS 67 TUTORIAL GROUPS. Work consisted of discussions between participants in smaJler groups and one or two of the lecturers Some evenifig lectures were given by the participants. These included H. Harre l l , R. Giintermann, and G. Zifonun, who presented ISLIB ('information System on a Linguistic Base), a system for answerifig questions to an input in restricted German, carried out at-.the Institut-fUf aeutsche Sprache at Mannheim. A. McKinnon 3f McGill University, Montreal. discussed his work on the Kierkegaard indices. Some lectures caused vivid discussibn. For example that of V. V. Raskin, Hebrew University, Jerusalem-, advocated corpus dependent semantic.models and recommended his own "f,estric~ed sublanguages" APPRECIATION

Altogether, tne tutorial in Lugana was very inspiring and profitable for the participants. It was well organized and gave good opportunity for discussions. The teachers in the tutorial being familiar w i th each other's work succeeded in giving a comprehensive view on the topic of computational semantics. some or us, .however, felt a need for more precise definttions of standard notions, this being a very acute problem in view-of the heterogeneity of the participants' backgrounds. We are, however, aware that this is an inherent and recurring problem at such gatherings, where people with different qualifications meet to dis-cuss comon problems We would like to express the wish tha-t the Fondazione dalle Molle w i l l be able to arrange more tutorials of a similar kind in the future. TUTORIAL ON COMPUTATIONAL SEMANTICS REFERENCES Charniak, Eugene. Toward a mode7 af children's story comprehension. AI-TR266, MIT Artificial Intelligence Laboratoryi 1972. Collinsv Allan M., and M. ROSS Quillian. Retrieval from semantic memory. Jou'rnal of. Verbal Learning and Verbal Behavior 8:240-247, 1969. Rewitt, Carl Planner: A language for proving theorems in robots. In Proceedings of the Interna tional Joint Conference on Artificial Intelligence, ed Donald Walker and L. Norton, 1969. Katz, Jerry A., and Jerrold Jo Katz. The structure of a semantic theory. Language 39:170-210, 1963.

McDeTmott, IY. V. Assimilation of new information by a natural language understanding system. AI-TR291, MIT ALtificial Intelligence Laboratory, 1974.

Minsky, Marvin. A framework for representing knowledge. AI-Memo

MIT Artificial Intelligence Laboratory, 1974.

Norman, Donald A. Memory, knowledge, and the answering of questiohs. Pn Contemporary issues in cognitive psychology: The Loyola Symposium, ed. Robert L Solso. V. H. Winston & I Sons, Washington, and Halsted Press Division of John ~ i i e & ~ Sons, New York, 1973. 135-165.

Norman, Donald A., David E. Rufnelhart, and the LNR Research Group. Explorations in Cognition- Freeman, San Francisco, 1975.

Palme, 3. The SQAP data base for natural Language information. Foa P rapport C8376-M3 (ES), Research Institute of National Defence, Stockholm, 1973.

Raphael, Bertram. Sir: A computer program for semantic information retrieval. In Semantic information processing, ed. Marvin Minsky. MIT Press, Cambridge, 1968. 33-134.

Rieger, Chuck J. Conceptual mewory. Ph, D. Thesis, Stanford University, 1974.

Scragg; Greg W. LUIGI: an English question answering program. MS, Center for Human Information Processing, University sf California, San. Diego, 1973. TUTORIAL ON COMPUTATIONAL SEMANT 1 CS Scragg, Greg W. Answering questions about pxocesses. Thesis; University of California, San Diego, 1974. Reprinted in part in Norman et al., 1975. Schubert, L. K. Extending the expressive power of semantfc networks. Proceedings O f the Fourth International Joint Conference on Artificial Intelligence, in press. American Journal of Computational Linguistics "FORMULAE" IN COHERENT TEXT : LINGUISTIC RELEVANCE OF SYMBOLIC INSERTIONS Respunsa Project Bar-Ilan Universi ty Ramat-Gan, Israel

Some difficulties in automatic analysis ~ n d translation bound to symbolic insertions in mathematical texts are discussed. Rules dealins with these difficulties are proposed, These rules are based on the use of the whole text of the a~Cicle incorporating a formula.

For satisfactory automatic analysis of texts, it is necessary to provide in the dictionary exhaustive serriantical Information ascribed to its entries. But this information can appear to be insufficient in cases where the meaning of! linauistic elements is ascribed to their occurrences by the very text in whlch they. are encountered cf . I or example, pronouns.

The other example is provided by symbolic insertions in mathematical texts, which we shall call 'If ormulaeN . So not only 'a= b , 'X 2 Y' etc., but also Ox* @ @ and so on are nforrnulaew. Mathematical formula resembles pronouns in one respect: it is semantically *voidqt being out of context. For example, @G9 may be *setH, "~ubset*, N~rouplt , %peratorn, Mfunctim*, "stringw, *elementu, 9qrule of grammarH, eto. The meaning is ascribed ta a formula by the context. There are a few types of fo~mulae with fixed meanings. F'or example, *dx/dyf Is @derlVatlve8. But this s l tb tion 1s not typical.

One of the basic usages of formulae conSist's of naming by formula A some individual object a belonging to some class b of objects such that there exists some noun block Cl(A) that names b.

For example, i'n the expression 'set R' the formula *R' names some individual set belonging to the class of %etsN-. Noun block @seta (consisting in this case- of a single -noun) names this class. So here c~(R) = *sete.

Consider some difficultAes arising in translation because of the absence in a source sentence of the Cl(f) for a formula E. Let US try to translate from, Engllcsh-to n\yn 'Russian the sentence Wcirst find an -- xmen t r of Rv. (1) (Previous surface syntactical analysis is, assumed, its results being represented in dependency-tr-ee form). Syntactically, this sentence (is very simple, but even an experienced "humanq* interpreter would not be able to properly understadd this expression and translate it.

h Russian. the element corresponding to the English preposition ?ofv is, generally, the grammatical meaning wgenltivell. We can ascribe this --- meaning to the formula *Rn [.governed by the prep~sitiorr 'of'): *We first find element r R + genitive'. (Syntactical links are also shown).

At ^this point, the process of translation is suspendea because of the fact that in Russian two non-coordinate formulae cannot depend on the same now. Similar examples are provicted by other languages:. German : In jeder Umgebung V von o X* . A human interpreter does not usually hesitate to properly translate such expressions only because he understmnds their meaning from a general background or vast context. We can point out some characteristic construe-tions in mathematical texts that are sufficient as contexts in such cases. Consider, for example, such a context.(i.e. an expression From the same text): 'Let R be a ring with a unity I*. (2 Ear expression (I), and let us formulate.;~very simple rules t *Let f bea N - Cl(f) = *Ne; (R 1 Here f is some flformulan, N - - a noun block, means icllb syntactical irnlr, reads: 'if . . . then*, and means substitutability. With the aid of the raes @'-i\ R and R we can 1 2 obtain from (1) and (2) the following expressions We first find /"4/3, an elect r 'of ring R which is easily translatable kr;, Russian: (The relevant syntacticaI links are shown; the two "f ormulaeN depend on different nouns ) . Of course, 'ri'ng R* Is not substitutable for R in the expression 'ring R' The expression *Components x are nonnegative * i ' w.ith the aid of the r e R 3' provides us O1(xi) and helps to translate the expression:

*A unique value Cf. also the contexts:

'Lgespaoe topolopique Ye and

mEln topoqener R am X* for the French and German examples abqve, s of x- i @ Let us now try to trans1at.e to Russian, the follow ing expressions:

'H is cyclic' (3); 'A smallest k* (4).

A predicative adjective in Russian must be put In grammatical agreement With the subject of the seritence; an attributive adjective - with the qoverning noun. That Is, the Russian adjectives for cyclicp In (3 ) and for *smallestm in (4) mus* asree in gender 75 with 'H' and *kt correspondingly. It is clear that the inf brmation about the gender of a I t f omulafl can be proyided by, Cl(f). Having defined. Cl(H) = 'matrixw for wh1chb..t;he translation 'KATRXTSAw is. remlnine, we receive for (3) the translation There exist numerous other ex,pre.ssions for which the finding of Cl(f) is very desirable, for example:

We deflne 3 and k by j = m + n; k = m - no. (5) The "direct* translation of (5) to Russian: 'Qpredeltm j i k putjorn j = m + n; k = m - nb is not smooth enough; the translation:

'Opredelim J i k s pomosh ju so~tn~shenij

3 =m + n; k -= m - n*, (*We ikefine j and k by correspondences j = m + n; k = m - n") is much better. ~l(f] can be f. For example, "inequalityqt, and formula f ban be to this formula or a prating f. sometimes defined from the very ) formula 'a = b' is nequalityl,, , , ,*a b" fs so on. Somet%mns t-he .he"meming18 of a

derived f rom words syntactically linked

from more complex fo2niula F incorFor example, from the e2presSion we can derive that T is a wtransformatianw and that A and @BW are wsetsM. From the expression we can derive that 'B' is a "setu and that 'ap is an 'Subset of A' A @ is a *.setN. In 'Differentiation IS (.or : integration.') w i th respect to xv, 'x' a l%arlabldN, and so on.

Cl(f) for a formula f can be sometimes a more or less bulky expression consisting of a noun w ith words depending on the noun directly or Indirectly. 'Tous les ensembles Li d indices lnferieurs a un nombre donne IS@ (c~(L~) is underlined). In this case we can reduce C1(L i ) to only one word *ensembles*. But in rare cases such reduction will produce absolutely inadequate translations,

Example t

In the expression

'Pour les fonctlons x(t) de Lg w i th a context

,La partie cornwe L de tous les ensembles Li ' (Cl(L) is underlined), we cannot reduce C1(,L) to only one word upartlee, which Is its syntactical governor,

'St is very difficult to formulate a general Pule ta discriminate between cases of typee (6) and (7). The expression. (7) om be translated using a synonym for C~(L), for example. 'ensemble', having in mind that the intersection of several sets is also a set. The computability of such synonyms can, of course, be questioned,

Now we shall consider some proDlems arising in translation of Russian mathematical texts into European and other languages.

The construction in Russian has two syntactical meanings, (a) appositive:, (b) genitive:' The cause of thls difficulty is the omission of Cl(f) in r;ne surfaoe syntactical structure of some Russian sentences: lpodmnozhestvo mnozhestva Bv- 'podrnozhestvo Bp "SubseT (of 1 set B" "Subset n (of) Bn. In such cases m e qenitive link is rare (5% of all occurrences of constructions of type N f, i.em several-dozen occurrences in a mathematical article). The task of automatic cho1c.e here is very difficult. It was solved only partially. We can ch~ose from the text of an article about 70% of all occurrences of the appositive links and also sowe occurrences of geni't-ive links, The rest of occurrences remain ambiguous.

The proposed procedures were checked in exhausting manual experiments, hue their aaaptation for computer is quite feasible. Choice Let us ax h oms (A 1 ) of appositive links consider the following empirically stated val id : In - the same Russian text every two different occurrences of t.he same expsre,ssion of type . N f are or both appositive or both So, if we have s-ucceeded in clarifying the meaning of a link in one occurreme of a construction, we can ascribe this meaning to every occurrence of the same construction. (A~) In a.construction of the type where fl and f2 are two syntactt;cally co- _T ~rdinate formulae, the two links are both

appositive or both qenitive. For example, havirlg a construction ("sets A and BH or '@sets of and 13") and knowing that in

'mnozhesf va Am the link is appositiye, we can consider the link in

*mnozhestva Be to also be appositive (1.e. "sets A and B").

(A 3 ) Let us call constructions of the type

f jest' N* and *oboznachim N cherez f* ( I*~e us t desiqnate N by f") introductory construotions. Every introductory construction ascr-ibes the meanizg to the formula which It introduces. n In every construc,ti.on N f, for which m. lntroductory construction exists in the same text. the (A 4 ) Sometimes the meaning is ascribed to a formula without any introductory con.struction.

The link n in an occurrence r of a construction f o f L t f e N the expression

f has not occurred in the text berore. r,. In this case the formu3.a f must also not occur before r as any coherent part (subformula) of some other formula F, Because t-Re meaning can be ascribed to a formula f by its place In F tsee above). Sut to use the distinction between a coherent and a non-coherent part of a formula (Cf. 'a + b' in '(a + b)/d8 and in 'ca +bd9), we need a calculus of' all mathematical symbolic notations, of which only small portions exist (Cf. arithmetic expresssionS 0f prograhming languages ) . Becaus-e of this Ah was formu1.ated in the above form).

(A 5 ) Sometimes there occur in mathematical texts expressions where verbal and symbolic parts are interwoven so that irl syntactic analysis a s-ymbolic insertion appears not as a single unit but as a complex construction having its own struct'ure. Some parts of tr formula can have links of their om wish the external verbal parts of the sentence. Examples : (tmFunotion L H(I1)" ). He re * is the predicate of .the sentence, 'Funstidn9 is iks subject and CH(R)* - an indi~ect object, The sentence Can be read as' 'F.unction L belon~s to H(EI)'*

Here 'belonging to'.

( "For every 1 6 B".. . ) is anmattribute *of 1 and can be read as

3. 'funktsija LE H(R) opredeljajetsjam..,.

"Function LO H(R) is defined by*... ) Here @ H(R) @ is an attribute of *Function9, and @t9 is an apposition modif-ying the same word. But the whole string L E H(R) can also be corlsidered an apposition modifying the word 'functioh' . So, we can formulate If in the type m -A a rule: the link some construction of N f Is apposiCt;'ve, then the link of the same N w i th the formula f R-- f * . where R 3. is one of the ~ymbo l s~ ,* ,< ,&~~ , ,3 .~ a.c,C.f.% or and f! is a (coherent) part of the formula f R f' Ls also appositive. The inverse also holds true. Using the axioms A1 to A5 cyclicly , we receive the 70% mentioned above. Example : Let us assume that the following Russi.an expresslions belong to the same mathematical text (and the preliminary syntactical analysis has already been done): (I) @Oboenachim etu tsepochku cherea A' ("Let us designate thsiS string by A" ) ; (2) 'tsepochki A i B = D@ ("strings. A and B = p"? Strlngs of A and B = D"?); (3 )

tsepochki B 1 F' ("strings B and Fw? "Strings of 3 and F"?);

tsepochka Fg

("string Fg'? "Stride; of

Using axioms A 39 A=, A29 kg* A19 can ascribe the meaning "appositive"

Assuming that In a text expressions (2), and (4) are present, and thar; the occurrence of @ in (4) 1s the f1rs.t; occurrence of this formula, we Can ascri3e to the (4) Fw?) Az and A1 we to the link in (4). 3 1 ink 'tsepachkl A' in (2) the meaning "appositive" with the aid of axioms A4, A1 A , A5 and A2 . So, we receive for expressio2s (3 ) to (4) translations: "strings -A and B = DM; *stxings B and FH ; *string F* It is worthwhile to mention that the same formula may occur in a text being linked appositively to several d%ffe,rent noms, for example,

'mno~oobrazi je it (l'manlfold a R* ) .

Different N in expressions of the type N -f (with the same f) can r'ef'er to each other as genus and species or can name obdects for which the fact of their identlty has been proven in the text. Using tho axiom A4 we can (very rarely) make an error. An error can occur in a case where the f~rmu la has the meaning specified once and for all independently from the text. So, wit,haut any previous definition of the meaning in an introductory construction or in a construction wftn tne apposftive link, a formula can at once be linked ~enit1vel.y to a noun. and

This situation is not typical in mathematical texts, Ih thls case we have a hieroqlyphio word (cf. '&', @$' in common Enqlish) and not a freely chosen notation. Such a word must be storea in the dictionary (wlth the 84 epecific meaning ascribed to it). For example, 'dx/dyW is 'derivativeq. Using Cl (f ) in every case of occurrence of e-yery formula, authors of mathematical cexts would nake the above procedures unnecessary. The problem qf standardizing the lanquage of scientifFc publications is not new, and in many cases some format of texts is prescribed. The problem of choos-ing occurrences of qenitive links in constructlons of the type - N f f rom the set of all occurrences af such constructions in mathematical texts and, also, of choosinq the only semantically relevant governor for a formmla which has several formally equivalent ones Is considered in (1). The qeneral procedure for resolving ambiguities in surface syntactical ). arialysis using broad context Is proposed in (2 I. S.A. q;jufmlsar~an, F.A. ~reizin, Z.T. Ter 9 * KI snk3;r~ts. at hem at ica~ ~ormqiae in Broad tontext, scientific & ~eohnicai Informati-on, series 2, No. 3. MOGC-OW, 1971, 33-38. 4 . . Y .A. ~reizin . A Cohputational Approach to the ~riofce of Analysis in the Case of Syntactic k'nb 9 1 --ui t J . Mech%n%cal ran slat ion and Applied Llnr_~.hstJ.cs. No. 10, Moscow 1967 pep. 3-20. American Journd of Computational Lhg~idics MScr~fiche .I7 . 86

All you ever wanted

to know about

afips constituent societies (but could never find.

in one place!) American Federation of Information Processing Societies. Inc. AFIPS CONSTITUENT SOCIETIES Contents. The Arnedcan Federation of lnformafion Processing Societies acts on behalf of 15 national organizati~ns engaged in the &sigh and/or application of computers and information processing systems. These societies range in areas of interest from the highest degree of technology in softwate and hardware to accounting and education, and they represent a tdtal memb e r a i n s of U&aaO,--- .Inherent in the relationship between AFfPS and its Constituent Societies are the aammon goals of promoting understanding between societies and the genaral public. This brochure provides a short overview of each societ& its goals, membership requirements, aatlvitles and publications. Every individual society has more extensive informatlon available for you, should you be rnterested in learning further about its specific areas of Intarest and expertise. Page:

7. lo.

Introduction American lnstitute of Aeronautics and Astronautics American lnstitute of Certified Public Accountants, American Society for Information Science American Statisticai Assobiation Association far Computational Linguisttcs Association for Computing Machinew Association for Educational Data Systems Data Processing Management Associatioh lEEE Computer Sbciety lnstitute of Internal Auditors Instrument Society of America Society for Computer Simulation Society for lndustrral and Applied Mathematics Society for lhformation Display Spedjal L ibclaries Association About AFIPS AFIPS CONSTITUENT SOCIETIES American Institute of Aeronautics and Astronautics (AIAA) American lnstitute of Certified Public Accountants (AICPA) Purpose AlAA Is an organization of people who have a cornmon intefest in space, the atmosphere and the sea. They see in the exploitation of these elements an opportunity to expand and enrich human life in countless ways and have set themselves to the study of the physical characteristits of these elements and to the develo~ment of machinery that will bring them more fully to humanvy's service, AlAA s objective is to the advancement of the' profession and the individual ih these pursuits. Membership Requirements All persons engaged in the profesbional practice of {hearts, sciences or technology of aeronautics, astronautics or hydronautics are eligible for,memberskip in AIAA: Others whuae work cantributes to the advancement of these fields are also eligible. Activities Each year AlAA sponsors or co-sponsors from 25 to 30 national meetings in different parts of the country at which AlAA members have an opportunity to hear, present and d~scuss pape'rs of importance to the advancement of aerospace science and engineering Many of the meetings include aerospace exhibits and field trips to nearby aerospace plants and laboratories. Publications Astronautics and Aeronautics AlAA Bulletin AlAA Journal Journal of Aircratf Journal of Spacecraft and Rockets Journal of Hydronautics Student Journal Reference Publications as warranted. Dues Members undei 30 ........................... Members 31 and aver .............. - . ~ . Student ..,,..,.. .............. Publications are extra, ,... .......................... $34 00 ~ 35.00 ~ .7.00 For Further Intormetion Contact: Dr. Jerry Grey American InstiFiute of Aeronautics and Astronautics 1290 Sjxth Avenue NeWYbrk, N. Y. 10019 Purpose The American Institute of Certified Public Accountants is the national professional association pf CPA s. The many activrties of the Institute are Uesigned to help member9 improve the quality of their professional services. the effectiveness with which they manage their practices. and their status as C;PA1s In the communities they serve. The Institute serves lo. unite the profession and to maintajn the staddards OF the CPA qualification aid the practice of accounting in the United States. Membership Requirements An applicant must be a-certified Public Accountant and be enga8ed in work teiated to accounting. Inte~ national Aseociate memberships are also available. ActiGi ties The Institute r annual meetings and conferences are a~med at keeping professional Issues and problems before its members. The Institute prepares and grades ihe CPA examination used thrbughout the United States and supports the Financial Accounting Standards Board which sets accounting standards. Other activities are promulgatron of auditlng standards, creation and administration of continujhg education courses and programs, establishment ef rules of professional conduct and conducting rnves ligations in connection with alleged violabions, maintenance of 3 Washington: D.C. office for haison with the Internal Revenue Service. Securities and Exchange Cornmlssion, and other federal agencies, monitoring of stgte legislation pertaining to CPA's, operatlon of an onI~ne, real-time computer-based ~nforrnation retrieval system,. and research into accounting, auditing and computer subject areas. " Publications The Journal of Accountancy - Monthly The Tax Adviser - Monthly The CPA Letter - Semimonthly Special techntcql publ~cations,.books, and pam~hlets. Dues Established by the Councll, dues aje levied on a graduatedscale, according to longevity as a CPA, pos~tion in practice. and occupationaJ status. For Further Information Contact: Donald L. Adams American lnstithte of Certified Public Accountants 121 1 Avenue of the Americas New York, New York 10038 CONSTITUENT SOCXETIES American Society for American Statistical bssociation (ASA) lnfdrrnation Sc~mce (ASIS) Purpase The AMerican Society for Information Science is a nonprofit national and professional association organized for scientific, literary. and educational purposes and dUicate4.to.the creation, organization. d~sseminalicn. and appncalion :of knowledge concerning information ana its Iransrer.:ASIS is dedicated to the imp~ovtment of the information-transfer process through research, development,. application gnd educatjon. The Society acts as a bridge between research and developq-ient and the requirements of d~vetse types of information systems. ASlS provldes a forum for the discussipn, publication and critical analysis of work deal~ng wUh the theory and practice of all elements involved in the cornmunicat~on of information. Membership Requirements Regular membership in ASIS-is open to any in-terested person who applies for membership and pays the prescribed dlles, No formal educational quallflcations for membership exist, Student memberships are available tor a period of'not more than three years to sersdns regylarly enrolled at a college or un~versity '9 In one or mom-courses ~f training or study for whiCh degree credits are given in the fblds of documentation. library science or in'formation scienee. Institutufional memberships are.also available. Activities The Annual meeting of the Soc~ety. usually held In October. provides a .focal point for the discussion oi formal papers and an Opportunity for informal talks with people of diverse ihterests. The Society alqo conducts a mid-year meeting. usually in May; part~cipates in programs of other professional societies: and, is an active partidpant in the National Computer Conference. AStS operates a member. placement service 'The Soc~ety has 24 major regianal. local chapters throughout the U.S., Canada and Europe. Publications Proceedings of the ASlS - Annual Journal of the ASlS - Bimonthly Annual Review of Information Sc'ience and Technology - Annual bulletin of the ASIS- 10 times a vear DWS Regular .............................................................. $ 35.00 Student .............................................................. 10.00 Institutianal Sponsor ..........-........-..-....-..--.._.._.._. 25030 For Further IMormation Contact:, Robert (Skip) McAfee, Jr.. American Society for Information Science 1155 16th St., N.W., Sulle,PIO Wesh'ington, D.C. 20036' 'Jurpqse 3uoting from the Cqnstitution of the ASA, "The objeclives of the American Statistical Association, a nonsrofrt organi'ratlon, .shall be to fester. In the broadest nanner, stat~stics and its applications, to promote ~nity and eifectiveness o,f Bffort among all concerned with statistical problems, end to increase the contribution of stAtistics to human welfare." The Association is composed of persons interested. in statMics, applied or theoretical. Through the Association, members mutually help each other w~th the exchange of professional Knowleam and tho reporting of new developments,,insuring twit stat~stlcal techniques 'discovered in one field are. made kdown to workers in'others, Membership Requirement5 There are several tyges of memberships available in ASA, including Regular and Institutignal. Contact ASA*Headsuart&s for further information on qualifications tor membels hip. Activities The annual meeting of the Association 'IS h,eld in August, typically in conjunction with annual meetings of other scientific societies-qoncerned dtth statistical practice. In addition. Ibwl rnaetkgs ar0 held by the ASA chapters and regional meetings are arranged when desired within the geographical districts into which the Association 'is divided. Since these meetings are smaller'th'an the annual meetings, they further opportunrties for still more intimate discussion on statistical matters of local or regional interest. Publications The Jaurnal of the American Statistical Associat~on -

Quarterly The American Statisticlans- Quarterly Newsletter - Tentimes yearly fechmmetrics - Qua-ifew Proceedinns - Annual ----~~$ular ................................... & . ................ $20,00 Student (Full-time) ................................. ...,....... 9.00 For Further lnformation Contact: Fred Leone American Statistical Association 806 15th St., N.W Washington, D.C. 20005' AFTPS CONSTZTUEN,T S JCI ETIES Assoc~at~on for Computatlcrnal Association for Computing Machinery (ACM) Linguistics (ACL) Purpose The Associatlon lor Computational l,inguistics $was founded in 962 by am rod^ bf researchefs wno shared a corhmon rnterest inmroad class of problems ihvolving both languages ana computation. Their purposes were:l(l) to promote research and development activities in tfie field pf computational fin'guist~cs, (2) to plomote cooperation and information exchange among related profess~onal and technital societies; (3) to represent computational llnguistlca to foundations and government agenues and lo represent tho United States to similar organizations in other nations and in international organlzatlohs which rncludc Cbmputa,tional lingulstlcs as a proper concern. Membership Reqyirements Any person fino IS intetested in computational llr~ guistics-is invited to ioin the Assoclatlon. Antlvi ties The Associatlon m#e?s.snnually. usually with the Nertional Cornputq~ Qonf.etsnce and Exposition or with, the Lingu~qic Soqiety of lcrmerica at 'their summer meeting. Publications The American Journal of Computational Linguist~cs, the primary journal of the Association, appears quarterly. The AJCL is piublished sn 4" x 6': units, each an ind-ek card or a miqrofiche. For each article, blbl~ography, or survey. two unlts are supplied - an index card bearlng a summary and a microfiche'conta~ning the full text. Announcements and advertisements appear on index cards. A yearly index is prov~ded on tabbed Index cards. Dues Individual ....................... jnstitutron ............ :. ...,.... ............. .... $10.00

25.00 For Further Inforqation'Contact: A. Hood Roberts ACL Center for Applied Linauistics 161 1 North Kent 6t. .Arlington, VA 22209 Purpose TO advance the sciences and arts of information proaessing includtng the study, designi development. construction, ana application of modern machinew. cbmputrng techn~ques and appropriate languages ror general information processing. storage, retrieval,and processing of data of all,kinds, and for the automatic. control and simulation or process. TO promote rrie rree interchange of informatlqn ahout the sciences and-arts of information prme~sing 1-0 develop and rnaiataln the lntegrlty ana competence of individuals engaged in the practlce 04 the sciences and arts: of information processing. Mernberlhtp Requirements Meniher: Persons qualified to be members: a) sups c r i~ the v purposes of ACM; b) have attained prafessi~nal statur,e as,denlonstrated by intellectual competence and ethjcal conduct In tlt'e hrts and sciences of ~nformation processing; c) have earnedla.8achelors Degr,ec or academlc i~ equivalent, or have four years' fulr-time experience rformatioq processing; d) are endarsed by two members of ACM and who attest to the above. Associate Member: Persons qualified to b.e associate memb-ers s'ubscrlbe to the purposes of the Associatlon. Student Members: \ndividuals registered in an accredited educational instltutwn full-t~me are qualified for student membershim Activities ACM conducts the Annual ACM Conference, the Annual Computer Science Conference, and partlclpates in the organization of t h National ~ Computer Conferences. In additfbn. reglonal and chaptet; meetings are held. SpeZial Interest Groups in a valrlety of disol: pllnes are also available to ACM members. Special Interest Group-s publisp mewslettprs and sponsor meetirrgs in their technical areas. There are over 240 chdolers and student chapters provid~ng locally spunsored programs. Publications r he journal or the Association fur

Computing Machinery - Quarterly The Communications of the ACM --Monthly Computing Revlews - Monthly Computing Surveys - Quarterly Transactions on Mathematicat Software - Quar tad) For Further Information Contact: Joseoh Cunninghatn Association for Computing Machinery T133'Avenue of the Americas NewYgrk, N. Y. 10036 AFIPS CONSTITUENT SOCIETIES &ssociatiop-for Educational Data Data Processing Management Systems (rC\EDS) Association (DPMA) Purpose The Association f~ Educatlorial r Data Systcn~S IS 't prlvdtc, nonprofit educational ory;rn~zation fotindcd In 1962 b,y a group of ptofoss~otlal P~lucalors dnd Iccllnical spoc~,~lists in oduc,ltion~l gppl~~atiohs. It:, intention 1s to provldcr ;I forum ldr tlio oxch;rllgc of irlcas and formation' about tfis ~clatlonsli~p ot'morltr~rl tcchrlofogy to modern educ'atlon. Membership Requirements AEDS membership is currcntry at 1,70U with mombctship open to all interested in learning more and keeping ~nformed about current dcvoloprncots ~ n directions in educational data Systems and computcl technology. Actiyi ties An annual international coofei'ence 1s held to brlng together key people from educat~o~i and t~'ctlnical specialists. Executives, adminlst~ators fiom all jcvols of education, and all fypes of research. m~inufdcturlng arid cammercl,~l servlcc ~Tganizatlons ntc' represented at th~s conference An annu~l computer programming contest is held for secondary scnool Students In gmdes 7-12.' The condesl is on the appfoved Ilst of cantests and acfiv111t.s published by, the National Assocmt~on of Secondary Schodl Frincipals. Local chapters regularly sponsor workshaps and seminars qn relevant toplcs dcslgned to advance edycation by develooing 'a greater awareness of the Impact dl educst~onal bctinology. Publications AEDS Monitor - Monthly AEDS Journal - Quarterly Convention proceedings - Annually AEDS Handbook and Membership Directory -

Annually to members only Large School Survey Layman's Gu~de to Use of Computers Dues Sfudent ........................... ,-... .... 5 10.00 lndjvidual.. ......................... ..., tn'stitutional. ...................................... Suskirnng ............... ,... .............. For Further Infomation. Contact: Shirley Easterwood Association for Educational.Data Systems 1201 7 6th St., N.W. Washington, D.C. 20036 d Purpose. DPMA is an organization serving the information processing arid computer management community. Among its primary qbjectlvgs RIQ: (1) oducation and ~esear ti ilctivitles focused on tho development of cffcclivc! mnnagen~eX programs for tho Sel.f-improvomr~~l~ of the membership, (2) encouragement of high standikrds of comp~tenco, and promotlon of n profess~onal nttltude among.th8 mombershir* and (3) fostering of a 6etfer understanding bf the vital business role of data processing !n society, and theproper relotionshlp of data processrng to management. Membership Requlrernents Membeshlp is granted onlf through a local chapte:, except in areas outsldc North America wherc tncrc is no chapter. Regutzf membership is grnntdd by the chapter. Board of Directors to persons engaged ..in managerial or supervisory po'sitions in data processing, educators, and executive personnel with a direct interest in dala .processing. Affiliate membersh~p may be granted by the Board to graduntesof an accredited college or university who are former members of o DPMA student organlzatlon: college graduates wlth one ya l ol EDP cxporlencc; or ~ndividuals whose major source of income is dlrect selling or lens~npof EDP equipment, supplies, or educational courses. Activities Tho Assbc~ation sponsors INFO1 EXPO. ' the annual lnternational Data Processing Conference and Business Exposrtion 'which -fentunes seminars, panels, workshops. special *sessions, on technical and cspccially management subjects. In add~tlon, DPMA "participates in the organization of thc National Computer Conference, Other programs and scrvlces offered by the Association include: regtonal conferences; individual chapter educat~onal meetings*; .v~deo tape seminars under chapter sponsorship featuring natronally known Industry experts, with- particular emphasis on management-oc~ented topics;-AIM (Advanced Instruction for Management) one-day. on-site semlnars cosponsored by chapters; and all-day chapter-sponsored seminars on Business & Management Pr~nciples. Publications Data Management - Monthly Special technical publ~cations, books, and pamphlets Dues International ............................ C-hapter .... ~. .............. ..., ............ Affiliate ........ .......,. ....................... $ 30.00

10-30.00

30.00 For Further Information Contact: Donn Sanford Data Processing Manaaement Association 505 Busse hlghway Park Ridge, Illinois 60068 12 AFIPS CONSTITUENT SOCIETXES IEEE Computer Soclety The Institute of Internal Auditors, Inn, (114 Purpose The IEEE Computer Society is actually part of a much larger organization. the lnstituta of Electrical and Electronics EnginrjsTs. Wlth so many spacial interests arnorg its members, it was natural for thoso who wanted to exchonga knowladga or who wished to concantlate on qne aroa of oloctronics to create Special lntorest Groups. The IEEE Camputor Society was formed to advdnco tho theory and the practice of computer and information processing techhbl~gy and ex change of technical informatlon among its members. The scope of the Society encompasses all asnects of design theory and practica relating to digitad hlld ana-

os devices, computation and information processing Membership Requirements You are eligible for Computer Society membership if you (1) are a member of the IEEE or an approved society: (2) have graduated from a 4-year course of study, or its equ~valent in a school of recognized standing; (3) have been involved professionally ir) the computer field for a period of at least flve years; (4) are A registered student interested insthe Society's field 04 interest.' Activities The IEEE Computer. Saciev sponsors tne Annua Computer Society Conference and parilcipatss in the organizat~on of the National Computer Conference. JF addition meetings for the presentation of tectinica papers and ldcal chapter meetings are hold regularly The technical committees sponsor many seminars symposia*and sessions for the benefit of its membership. They also arrange the Distinguished isitors Program which prov~des loi leading computer professionals to speak to the local cnapters of the Society and educational institutions. Publications Computer Magazine - Monthly Transactions on Computers - Monthly Transactions on Software Engineering - Quarterly Proceedings (and special bdoks as warranted) Dues lEEE Members ..................................... ..........., $ 6.00 Non-members applying to

IEEE Compuier Society and IEEE

U.S. and Canada ......,.. .............................

Other Countries .% . ..................................... Affiliate Membership For Further Information contact: Harry Haymah P.O. Box 639A Silver Spring, Maryland ,20901 . ..... 24.00 Purpose The InstiWtrr of Internal Audlto s 1s an international organization dedicated to the advanccrhcnk ot the professloh of internal auditing. The Instlhte ,zcks the enrichment of ks rnembhrs through the'interchrtngo nf ideas, tnforma~lon and contacls. It 1s dedicated to niaintn~ning fhq highost po9sible stdndards of competence, morality and dign~ty in the professjan Membership Raquit ernents All praC1lClnQ internal auditors, thgse resp~nsible for the funct~on, publ~c accountants, educators. and auditing students are ~nvited to join The Institute. Activities The lnstltute offers many benefits to its members through a wlde variety of services frdm its international headquarters and its chaptgr orga~lrations. In the fleld of EDP audlt~ng, in particular. a spectal* department helps the aud~tor keep up wlth this changIng field and provides hard-to-locate EDP aud~ting Infdrmatron. An "EDP Systems" department in the Instc tule's award-w~nning b~monthly technical journal, The Infernal Auditor, and a nionthly EDP-updating service, EOPACS, are additional helps published for those involved irrthe audit and control sf EDP systems. A continuing program of gemlnars, woykshops, and lectures conducted by the Cadmus Education Foundation of The Insfltute, along w~th annual area and lnternat~onnl conferences, serve to keep the internal auditor "on top" of the latest developments in techniques and practices ~r Yhe t field. An examlrintion in internal aud~trng and related subjects is offered to those who nieet certaln equirements. Those quafrf~ed will be entitled to use the profess~onal designation of 'Cert~fied Internal Auditor (CIA). The Institute also publishes research reports on such toplcs as electrmic data pl ocessing, statistical sampling. ~n.sentory csntroi, organ~zational control, and the'behavlorai selences. Publications The Internal Auditor - Bimonthly Aud~t~ng News - six times a year Edpacs - Monthly Spec~al researdh reports and books Dues Member or Associate Member .................... , . $60.00 Educational Associate ............................ 26.00 Retired Member ............................... .,.. 13.00 Student Member ................................ 10.00 For Further Infurmation Contact: Williaw E. Perry: CIA The Instdute of Internal Auditors, lne 5500 Diplomat Circle Orlando, Florida 32810 AFIPS CONSTITUENT SOCIETIES Instrument Society of America (ISA) ~oclety for Computer Simulation (SCS) Purpose The Instcumant Society of America is a nonprofit scientific, technical and educational organization dedicated to advancing and reinforcing the arts and Bclencas related to the rheoty, design, manufacture and use of instruments and controls In tho varloos sciences and technologies for the benefit of mankind Membershlp Requirements The types of memberships available in ISA are predicated upan specific Individual quatificatians. Senior Membership requites either a B.S, or engineerlng degree and at least six years work in instrumentation, two years having been in a position of responsible charge; or no degree but ten-years work in instrumentation, two years having been in a position of responsible charge. A Regular Membership is open to any persgn interested in instrumentatian and the programs of the Sociefy. An Associate Membership is limited to those whose principal interests and occupations are not specificaUv in instrumentation. Student Members are either enrolled as iull-time students or enrolled in a formal spprenticeship course. Activjties The scope of Society activities embraces these areas of instrumentation: aerospace, analysis, automatic control systems, bb-medical s.ciences, chemical and petroleum, cryogenic thstrumentation, data handling and computation, food, maintenance, marine sciences metals, metrology, mining and metallurgy, power process measurement and control-, pulp aad paper scientific instrumentation and research, telemetry test tneasurernent, textile and tranwortation. ISA publishes and disseminates information develobs standards; conduct$ conferences, symposia ana exhibits: providas educational services and honors'indi. vidwl achievement. Publications Instrumentation Technology - Monthly Proceedings - Annual Advances in Instrumentation - Quarterly lSAf ransactions - Quarterly Special ~ubiications - As warranted Dues Senior Member Regular Member .............................................. Associate Member ..... .........,.... .................... Student ................................................................ ................................................ F-ar Further Information Conlact: Executive Director Instrumentation Society of Ameriob 400 Stanwix Street Pittqburgh. Pa. 15222 $26.00 5.00 P~lpvrr: Tha Society fo~ Computer Simulation is the principal tochnical spciety devoted to the aclvancoment of simulation thtougb tho uso of computars and similar dovicas whloh gqploy mithctnatic'ill or physicnl analogies. The purposo of SCS is to promota the Ilevoiop: men! of,simulatlon tecl~nology I~I and'to wldon its appli- cation i,n all fields. most of its activities SCS seoke to accompl~sh lheso ends through tho exchange of information among people who ate using simulation to advantage in their endeavors. Membership Requ1rer)lents Full membership IS open to people who have been professionally engaged in any phase of simutat~on and allied computer techhology for at least four years. This requiremerit may be met by graduation from a four-year course of study in an approprlatc field of scienoe, engineerlng, or mathematics at an accred~ted institution of hrgtier Jearoing or by its equivalent Associate Membershlp In fbe Socie!y IS available to anyone who is interested in the technology of s~mulatioh or in applicat~~ns of the computer arts and scienC8S. Student Mombershjps are open to any oerson egularly enrolled on a substantially full-time basis in an institution of higher learning, including graduate student$ who hoJd teaching fellowships, upon certllication of their status by a member of the faculty of such institution. Activl ties SCS co-sljonsors the Summer Computer Simulation Conference and the Winter Simulation Conference, and participates in the ~rgani~atbn- of the ~ati0nal Computer Conferences. Individual Reg~onal Colrncil meetings present papers and panels on selected topics and offer attendees an opportunity to' take guided tours of the hosting organ~zatlon's s~mulat~on facilit~es Puljlica tions Simulation - Monthly Procegdings - Semiannually Dues Full hember ............................................. $25.00 AsSociateMember ........................... . .............. 25.00 Undergraduate &.:Graduate Student Member 15.00 Senior Member. ....... Speclal A~~l~cation Necessary For Further Information Contact: Alex McKenn8 The Societv for Computer S~mulation P,O. box z2228 La Jolla. California 92038 FIPS CONSTITUENT SOCIETIES Society for Industrial and Applied Mathematics (SIAM) Society for Information Display ISID) Purpow The Society for Industrial and Applied Mathematlcs was formed in 1952 lo furtlier the applications of mathematics to problems in industry and science Rccognizing the gap in a professional structulo where the ropid expansion of industrial research had crentod a need tot basic analytical thought and n6w mathemutical methods, S-AM developed new media to br~dge this gap and foster the exchange of ideas among ali who are interested in theapplicatlons of mathematics Membership Requirements Membership In SIAM is available to those people intetested in the goals and objectives af the Society. Formal applications are directed to a Membership Committee for approval. Activities SlAM conducts two national meetings edch year in the Spring anti Fall Such meetings are structured on a aentral theme to discuss an important and timely subject in mathematics In addition, with the support of the National Science Foundation, the Office of Naval Research, and the Air Force Off~ce of Scientific Research, SlAM sponsors special international symposia bn various topics in mathematics. SlAM also created the SlAM Institute for Mathematics and Socfaty in January 1973 to foster the application of mathematics to the major problems of socrety. Publications SlAM Journal on Applied Mathematlcs -

2 volumes per year, 4 issues each SlAM Journal on Computing - Quarterly SlAM Journal on Control - Bimonthly SlAM Journal on humerical Analysis - Elmonthly SlAM Revlew - Quarterly SIAM Journal of Mathematical Analysis - Bimonthly Theory of Probability and Its Applica!ions - Quarterly SlAM News - B~rnonthly~ Dues Regular Members -.. ............... a .............. $22.00 Student Members ....... ............... 10.00 For Further Information Contact: R. K. Windsor Society for Applled and Industrial Mathematics 33 South 17th Street Philadelphia, Pa. 19103 Putyose The Society for lnformation Display was chartered Bs a nonprofit technrcal corpolation In 1962. wtlh me iollowing goals and purposes: Encouragr, and contflbute to the sc~cnl~f~c udvancemcnt of Information DlsplBy Promob the yse ol I'nformatlbn 01splay Maintain a central file ~f d~splay ~nformatrun for use by members Prov~de forums for the exchange end dlssemlnatlon of ideas and knowledge related to lnformatlon Display Promulgate debnitionsand standards pertalnlng to the field of Information Display Stimulate new idees in Information Display and foster their develppmeht, Membership Requirements Current rnembersh~p in SID is approximately 2.000 and is open to ail who can. benefit from the Soc~ety and wish to further ils goals. Membership is open to both ~ndividuhls and companies. Activities The Socrety sponsors an Annual Technical Symposlurn and occasional shorter meetirigs. In addition, all SID members are afflllated with one of ten local chaptors located throughout the world, which serve as the focaf points of regular technical meetings, tbld trips, seminars. and tutotiats, Members are, encouraged to part~cipato in all Society activities and ta present their jechhical achievements and views in 6lD publlCations. Publications Proceedings of the SID - Quarterly SID Journal - Bimonthly Symposium Digest --AnnuatDues Member arid Associate .................... ..; .... S 15.00 Sustaining. .......................................... 150.00 Student (full-time) .................... ..-....... .. 3.00 Proceedrngs not included For Further Information Contact: VSolet Puff Sooiety for lnformation Display 654 North Sepulveda Blvd. Los Angeles. Ca 90049 AFIPS CONSTITUENT SOCXETIES Special Libraries Association (SLA) Purpose The Association encourageB ana promotes Ine utilization of knowledge through the collection, organizatlon end dissemination of information, SLA is an association of Individuals and or~onlzations with educational, scientlfio and tschnica itltereqts in library and Information science and tc hnology, especially as these are applied to the sell ctldn, recording, retrieval and effective utlliration jf man's knowledge Speclal libraries serve Industry; business, -esearch, educational and technlchl institutions, govarnment, special departments of public and university libraries, newspapers, museums, and all ot'ganlzatians, both public arrd private, requiring or providing specialized Informatioh, SLA and its members are Gancernea wrtn tne aauancement arrd improvement of the communication, dissemination and ultlrnate use of information and knowledge for the general welfare and the advancement of mankind. MemDersnip Requirements Membership category depends on the applkant's background. Members are assigned to the highest membesshjp class for which they are qualified, Application4 may be obtained from the Association's office In New York. Activities The Special Libraries Association holds an Annual Conference in June, which lnoldde's sessions of both general and Specifi~ prabskiond interests, discussion of new equipment and technolasy, division arogram and business meetings field trips to outstanding special libraries and informatton centers, conttnuing education seminars, and an extensive exhibit area. Putilications Speclal Libraries Scientific Meetings 'Technical Book Review Index. Books and Monographs Dues Regular ...................................................... $ 30.00 Associate .......................................................... 30.00 Stukient ............................. .. ........................ 8.00 Retired ...................... ttttt.ttttt.tt...........,_ ...................... 10.00 For Further lhformation. Contack Dr. Frank McKenna Special Librafies Association 235 Park Avenue South New York, N. Y. 10003 About AFIPS The ,American Federation of lnformation Processing Societies represents 15 natlonal organlzatio~s engaged in the design andlor application of computers and information processing systems. Dedicated to nonprofit scientific and educational purQoses, the Federation acts In behalf of tFfese Constituent Societles irl cat'rying out programs designed to advance lnformatlon processing as a rasponsiblo profession. Its primary objectives Include: Undertaking of joint information processing activities on hehalf of its Constituent Societles Promotion of cooperation and information exchange among professional and technical secieties, governmental organizations, and nonpolitical lnternational gtoups

Participation In nonprofit International organizations

concerned with computers and information

processing * Undertatiing of research and development activities

ih the information processing field * Provision of servi.ces to Constituent Societies Dissemination of reliable information on'lnformation processing and its, progress to interested groups and to the generai pabric In addition fo the National Computer Conference L Exposition which is sponsotwd annually by AFIPS ACM, DPMA, IEEE-CS and SCS, the Federation also sponsors confemnccs, seminars and symposiq on behalf of its membershipaand maintains a major Washington activities progrw. AFIPS Press publishes the Proceedings of the National Computer Conference, irl addition to the Proceed~ngs of special seminars and symposia, statistical research reports, and information booklets. Educational projects include the development of career inf~rmation, ass~stance in the development of educational guidelines,and teacher training programs, and a Computer Internship~Program designed to assist developing countris. important programs are continually being carr~ed out by the Public lnformation office, the Statistical Research and the S6cial Implications Programs. On the international scene, AFIPS is the U.S. representative to the international Federation for Information Processing and participates actively in the IFlP Group for kdntinistrative Data Processing (IAG).