O‘ZBEK TILIDAGI MATNLARNI VEKTORLASHTIRISH USULLARINING SEMANTIK O‘XSHASHLIKNI ANIQLASHDAGI SAMARADORLIGI
DOI:
https://doi.org/10.65164/2pypxe85Ключевые слова:
matn vektorlashtirish, semantik o‘xshashlik, TF-IDF, Word2Vec, FastText, BERT Transformer modellar, tabiiy tilni qayta ishlash, o‘zbek tili korpusi, benchmark, lemmatizatsiya.Аннотация
Mazkur maqolada o‘zbek tilidagi matnlarni sonli ifodalash (vektorlashtirish) usullarining samaradorligi qiyosiy tahlil qilindi. TF-IDF, Word2Vec, FastText hamda BERT arxitekturasi asosidagi Transformer modellari o‘zaro taqqoslandi. Eksperimental tadqiqotlar 193000 dan ortiq hujjatdan iborat maxsus matn korpusi hamda 4200 ta belgilangan (annotatsiyalangan) matn juftliklaridan tashkil topgan baholash to‘plami asosida amalga oshirildi. UzBERT modeli F1 = 0,92 ko‘rsatkichiga erishib, tadqiqotda ko‘rib chiqilgan boshqa usullarga nisbatan yaxshi natija qayd etdi.
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