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Abstract <p>Efficient extraction of named entities is essential for data analysis, especially given the increasing volume of textual information. This study examines and compares methods for extracting named entities within text-processing algorithm for excursion data, offering statistical insights into events described in natural language texts, which include brief information about the excursion name and its target audience. The practical results highlight the applicability of these methods in supporting and enhancing JINR’s internal services, particularly the JINRex system for excursion planning and management.</p>

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Practical Comparative Analysis of Named Entity Recognition Methods for JINR Digital Services

  • 期刊论文

  • 发表日期：

    2025年10月3日

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  • A. Il’ina

摘要

Abstract

Efficient extraction of named entities is essential for data analysis, especially given the increasing volume of textual information. This study examines and compares methods for extracting named entities within text-processing algorithm for excursion data, offering statistical insights into events described in natural language texts, which include brief information about the excursion name and its target audience. The practical results highlight the applicability of these methods in supporting and enhancing JINR’s internal services, particularly the JINRex system for excursion planning and management.