Named Entity Extraction Model Based on the Random Walk Method

Madina Mansurova, Vladimir Barakhnin, Marzhan Kyrgyzbayeva, Nurgali Kadyrbek

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

In connection with the rapid development of Internet technologies, modern society in recent decades has experienced an information explosion characterized by an exponential increase in the volume of information, including low quality information. This work is intended to provide all interested parties with intelligent tools to support decision-making by automatically extracting knowledge from heterogeneous data sources, including the Internet. In the work, we examined the primary processing and morphological analysis of texts, implemented a random walk method to extract semantically related words. As a result of the calculations, we got a matrix with the affinities of words, as well as a dictionary that connects the word with the vector component. In addition, the neural network, trained to retrieve linguistic constructions, which include the possible values of descriptors of named text entities, was described in the work.

Original languageEnglish
Title of host publicationSIST 2021 - 2021 IEEE International Conference on Smart Information Systems and Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728174709
DOIs
Publication statusPublished - 28 Apr 2021
Event2021 IEEE International Conference on Smart Information Systems and Technologies, SIST 2021 - Nur-Sultan, Kazakhstan
Duration: 28 Apr 202130 Apr 2021

Publication series

NameSIST 2021 - 2021 IEEE International Conference on Smart Information Systems and Technologies

Conference

Conference2021 IEEE International Conference on Smart Information Systems and Technologies, SIST 2021
CountryKazakhstan
CityNur-Sultan
Period28.04.202130.04.2021

Keywords

  • named entity extraction
  • neural network
  • random walk method

OECD FOS+WOS

  • 1.02 COMPUTER AND INFORMATION SCIENCES
  • 1.02.ET COMPUTER SCIENCE, INFORMATION SYSTEMS

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