Models for effective categorization and classification of texts into specific thematic groups (using gender and criminal themes as examples)
2024 (English) In: CLW-CoLInS 2024, computational linguistics workshop at Colins 2024: proceedings of the 8th international conference on computational linguistics and intelligent systems. Volume IV: computational linguistics workshop, Lviv, Ukraine, April 12-13, 2024 / [ed] Nina Khairova; Victoria Vysotska, CEUR-WS , 2024, Vol. IV, p. 37-49Conference paper, Published paper (Refereed)
Abstract [en]
An analysis of existing automated methods for text classification, used to develop an effective approach for automated text classification by thematic groups in the context of information related to criminal and gender themes, was conducted. Based on the analysis of classification methods, an algorithm for classifying texts by types of crime and gender was developed, information-linguistic and software for the task of distributing texts into thematic groups were developed, and the effectiveness of the developed application was assessed.
Place, publisher, year, edition, pages CEUR-WS , 2024. Vol. IV, p. 37-49
Series
CEUR Workshop Proceedings (CEUR-WS), ISSN 1613-0073 ; 3722
Keywords [en]
categorization, Classification, criminal justice theme, gender criminology, gender stereotypes, social practices, thematic groups
National Category
Natural Language Processing
Identifiers URN: urn:nbn:se:umu:diva-227967 Scopus ID: 2-s2.0-85198743336 OAI: oai:DiVA.org:umu-227967 DiVA, id: diva2:1885255
Conference CLW-2024: Computational Linguistics Workshop at 8th International Conference on Computational Linguistics and Intelligent Systems (CoLInS-2024), Lviv, Ukraine, April 12–13, 2024
2024-07-222024-07-222025-02-07 Bibliographically approved