There aie only few Russian vocabularies in coaputemed fore in the DSSfi now, so development of a new Russian vocabulary large enough for spell checking is still topical.

The requirements for such a vocabulary are at least as follows : ii sore than 100,000 lexemes included; 2) siodern and diversified lexicon well covering the sciences, aany technological fields, the huaanities, and may be the everyday life; 3) mapping the sost of nuserous lexeie foras implied by the flectional nature of Russian, and at the saae Use acceptance of well-foraed words only: 4) orientation to IBH-cofipatible PCs sost coauonly used in the USSE nowaday.

Such a vocabulary has been recently built by the author, Its parameters are as follows: 6?,W0 stens covering sore than 104,700 Russian lexeaes and their 1,425 œillion word-forits (i.e. 21.2 foras/stea); the Biaisai, the Bean, and the aaxinal stea lengths aaounting to 1, 7.8, and 32 letters accordingly; the textual fors size being about 865 KB.

Our aorphological classification of steas is quite original and deals not only with word formation, but also with word derivation. The scheae includes 118 classes and 1901 various flections (variable suffixal chains). Separate classes sere introduced among aentioned ones for invariant words, irregular foras, and abbreviations, The first 38 classes cover more than 835! of all steas.

The split borders of steas sere freely moved to the left while classifying, if aorphological alternations or identical final letters in a whole stea class have been encountered, The shortest flection is an eapty one, the longest flections include up to 12 letters (e.g. HP0BÄBBHÄHC8), so the aean flection length grew up to E letters, which is comparable to the mean stem length.

The textual fors of vocabularies is not convenient for applications and has to be transformed into binary working fora. The Hell known archivization packages such as PKARC/PKXARC are not acceptable for this purpose because of low squeeze ratio and uselessness of the archivized fora as a working one for spellers or any other application, So several other methods of compression were analyzed,

Basically the Ruffian method has been selected for coding aorphological class nusbers, and the Cooper aethod has been picked up for the stess, Additionally the RADIX-50 aethod was applied to both of the components of a vocabulary entry.

Several other techniques are turned out to be useful for additional stea cospression in large vocabularies. They are based on 11 frequent recurrences of differently classified, but literally identical steas; 2) coMoness of events in nearly saturated vocabularies, when the first letter in the deflecting part of a stea is alphabetically adjacent to the letter is the saae position within previous stea; 3) availability of several free positions in SASIX-50 code table (only 33 of 40 are grasped by Russian letters and a delisiter}. These unoccupied values sight be used for re-coding final stea letters, digraas, and trigrass sost frequent in different stea classes. This technique squeezes the letter part of a vocabulary entry and sake the deliaiter preceding the next entry unnecessary,

All aethods lentioned were investigated, separately and in combinations. The Huffsan's 4- the Cooper's + RAD 11-50 coabination has given us a sqeeze ratio about 3.4, whereas addition of the rest techniques has increnented the ratio up to 4.2 - 4.5. So only about 190 KD in aeaory is needed for this working fora, which is easy ailocatable as a resident part of a todern text processor, As coipared to vocabularies in available English language spellers, the size achieved seeas to be highly competitive in our aore cosplex inflectional case.

The vocabulary is available both in the textual and in binary forss. Several utilities concerned with its coapiling, debugging, and squeezing are ready too. The utilities were written using Turbo Pascal 5.0 and Turbo Professional packages and are wholly applicable for processing any other natural language vocabulary,