MATNLI MA’LUMOTLARDAN FAKTLARNI AJRATISH TEXNOLOGIYALARI

This is an outdated version published on 2025-04-18. Read the most recent version.

MATNLI MA’LUMOTLARDAN FAKTLARNI AJRATISH TEXNOLOGIYALARI

Authors

  • Niyozmatova N.A “Toshkent irrigatsiya va qishloq xo‘jaligini mexanizatsiyalash muhandislari instituti” Milliy tadqiqot universiteti qoshidagi Fundamental va amaliy tadqiqotlar instituti
  • Xoitqulov A.A “Toshkеnt irrigasiya va qishloq xo‘jaligini mеxanizatsiyalash muhandislari” Milliy tadqiqot univеrsitеti
  • Mamatov A.A Namangan davlat universiteti

Keywords:

Faktlarni ajratish, matnli ma'lumotlar, tabiiy tilni qayta ishlash, mashinali o'qitish, semantik tahlil, nomlangan entitetlar, ma'lumotlarni tuzish, qoidalarga asoslangan yondashuv, validatsiya, strukturalashtirish.

Abstract

This article analyzes the technologies for extracting facts from text data and
their importance. The article considers methods for extracting facts from texts accurately and
efficiently, including keyword-based extraction, rule-based approaches, and machine learning
methods. Along with natural language processing technologies and semantic analysis methods,
the main stages of extracting facts are covered - the processes of identifying named entities,
extracting relationships, identifying events, extracting facts from text, and validating them. It is
emphasized that today the issue of processing large volumes of text data, extracting useful
information from them, and structuring them is of great importance in optimizing decisionmaking
processes in various fields such as medicine, law, and business.

Downloads

Published

2025-04-18

Versions

How to Cite

Niyozmatova N.A, Xoitqulov A.A, & Mamatov A.A. (2025). MATNLI MA’LUMOTLARDAN FAKTLARNI AJRATISH TEXNOLOGIYALARI. MANAGEMENT AND ECONOMICS SCIENTIFIC RESEARCH JOURNAL, 2(2), 178–180. Retrieved from https://journals.timeedu.uz/index.php/mesr/article/view/380

Issue

Vol. 2 No. 2 (2025)

Section

Articles