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Abstrakt
These days, a lot of crime-related events take place all over the world. Most of them are reported in news portals and social media. Crime-related event extraction from the published texts can allow monitoring, analysis, and comparison of police or criminal activities in different countries or regions. Existing approaches to event extraction mainly suggest processing texts in English, French, Chinese, and some other resource-rich and well-annotated languages. This paper presents a parallel corpus-based approach that follows a closed-domain event extraction methodology to event extraction from web news articles in low-resource languages. To identify the event, its arguments, and the arguments’ roles in the sourcelanguage part of the corpus we utilize an enhanced pattern-based method that involves the multilingual synonyms dictionary with knowledge about crime-related concepts and logic-linguistic equations. The event extraction from the target-language part of the corpus uses a cross-lingual crime-related event extraction transfer technique that is based on supplementary knowledge about the semantic similarity patterns of the considered pair of languages. The presented approach does not require a preliminarily annotated corpus for training making it more attractive to low-resource languages and allows extracting TRANSFER, CRIME, and POLICE types of events and their seven subtypes from various topics of news articles simultaneously. Implementation of our approach for the Russian-Kazakh parallel corpus of news portals articles allowed obtaining the F1-measure of crime-related event extraction of over 82% for the source language and 63% for the target language.
Cytowania
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2
CrossRef
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0
Web of Science
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1
Scopus
Autorzy (5)
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Nina Khairova Professor
- Umeå University, Sweden
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Orken Mamyrbayev Associate Professor
- 3Institute of Information and Computational Technologies, Kazakhstan
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Mariia Razno M.S
- 5Institut für Slawistik und Kaukasusstudien, Friedrich Schiller University Jena, Germany
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Galiya Ybytayeva M.S.
- 6Department of Cybersecurity, Information Processing and Storage, Satbayev University, Kazakhstan
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Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1109/ACCESS.2023.3281680
- Licencja
-
otwiera się w nowej karcie
Słowa kluczowe
Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuły w czasopismach
- Opublikowano w:
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IEEE Access
nr 11,
strony 54093 - 54111,
ISSN: 2169-3536 - Język:
- angielski
- Rok wydania:
- 2023
- Opis bibliograficzny:
- Khairova N., Mamyrbayev O., Rizun N., Razno M., Ybytayeva G.: A Parallel Corpus-Based Approach to the Crime Event Extraction for Low-Resource Languages// IEEE Access -Vol. 11, (2023), s.54093-54111
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1109/access.2023.3281680
- Źródła finansowania:
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- Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan under Grant AP09259309
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 276 razy
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