OʻZBEK TILIDAGI MATNLARNI TAHLIL QILISHDA NOMLI OBYEKTNI TANIB OLISH (NER) YONDASHUVI

Kenjayev Xamdam Bazarbayevich

Authors

Kenjayev Xamdam Bazarbayevich Nukus davlat texnika universiteti

Keywords:

tabiiy tilni qayta ishlash, nomlangan obyektlarni tanib olish, NER, mashinali o‘qitish, chuqur o‘rganish, gibrid yondashuv, matn tahlili, semantik axborot

Abstract

Ushbu maqolada o‘zbek tilidagi matnlarni tahlil qilish jarayonida nomlangan obyektlarni tanib olish (Named Entity Recognition-NER) yondashuvlari har tomonlama tahlil qilingan. Tadqiqot doirasida NER tizimlarining nazariy asoslari, qoida asoslangan, mashinali o‘qitishga asoslangan hamda gibrid yondashuvlar batafsil ko‘rib chiqilgan va ularning afzalliklari hamda cheklovlari solishtirma tahlil asosida yoritilgan. Shuningdek, turli tillar va sohalarda, jumladan tibbiyot, oziq-ovqat va axborot tizimlarida qo‘llanilgan zamonaviy NER modellarining ishlash samaradorligi tahlil qilingan. Tadqiqot natijalari NER tizimlarining katta hajmdagi matnli ma’lumotlardan semantik axborotni avtomatik ajratib olishdagi ahamiyatini ko‘rsatadi hamda kam resursli tillar, xususan o‘zbek tili uchun moslashuvchan va samarali NER modellarini ishlab chiqish istiqbollarini belgilab beradi.

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