MATNLI MA’LUMOTLARGA DASTLABKI ISHLOV BERISH ALGORITMLARI
Kalit so‘zlar:
Matnli ma’lumot, dastlabki ishlov, TF-IDF, so‘zlar sumkasi modeli, vektor fazosi, Word2Vec, CBOW, Skip-Gram, semantika, normallashtirish, to‘xtash so‘zlar.Annotatsiya
Maqolada matnli ma’lumotlarga dastlabki ishlov berish jarayonining
algoritmik asoslari tahlil qilinadi. Dastlab HTML teglar, to‘xtash so‘zlar, tinish belgilar va
o‘zaklash kabi usullar orqali matnni tozalash bosqichlari ko‘rib chiqiladi. Matnni raqamli
ifodalash uchun TF-IDF, so‘zlar sumkasi modeli, vektor fazosi modeli kabi klassik usullar
yoritilgan. Shuningdek, Word2Vec, CBOW va Skip-Gram kabi neyron tarmoqlarga asoslangan
zamonaviy modellar bilan tanishtiriladi. Bu modellar yordamida matndagi semantik bog‘liqlik va
kontekst saqlanadi, bu esa matnni chuqur tahlil qilish imkonini beradi. Maqolada algoritmlarning
nazariy asoslari hamda ularning real sohalardagi qo‘llanish imkoniyatlari ham yoritilgan.
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