Cited By
View all- Xu KFeng YLi QDong ZWei J(2025)Survey on terminology extraction from textsJournal of Big Data10.1186/s40537-025-01077-x12:1Online publication date: 6-Feb-2025
TermoPL: a tool for extracting and clustering domain related terms
Article No.: 39, Pages 1 - 4
Abstract
We present a new version of the terminology extraction tool - TermoPL. This version not only allows the ranking of term candidates but also their semantic grouping. To ensure the results are precise, we use the WordNet lexical database for identifying semantic relations between words. The tool was designed primarily for Polish texts, but the current version is tagset-independent and can be adapted to process texts in other languages. The new semantic grouping feature has been fully implemented for Polish texts, but we plan to make it available for English texts as well.
References
[1]
Gerlof Bouma. 2009. Normalized (Pointwise) Mutual Information in Collocation Extraction. In Proceedings of the Biennial GSCL Conference. Tübingen, 31--40.
[2]
Hernani Costa, Anna Zaretskaya, Corpas Pastor Gloria, and Míriam Seghiri Domínguez. 2016. Nine terminology extraction Tools: Are they useful for translators? MultiLingual (2016).
[3]
Damien Cram and Béatrice Daille. 2016. Terminology Extraction with Term Variant Detection. In Proceedings of ACL-2016 System Demonstrations. Association for Computational Linguistics, Berlin, Germany, 13--18.
[4]
Béatrice Daille. 2017. Term variation in specialised corpora: characterisation, automatic discovery and applications. John Benjamins Publishing Company, New york.
[5]
Agnieszka Dziob, Maciej Piasecki, and Ewa Rudnicka. 2019. plWordNet 4.1-a Linguistically Motivated, Corpus-based Bilingual Resource. In Proceedings of the 10th Global WordNet Conference: July 23--27, 2019, Wroclaw (Poland), C. Fellbaum, P. Vossen, E. Rudnicka, M. Maziarz, and M. Piasecki (Eds.). Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław, 353--362.
[6]
Katerina Frantzi, Sophia Ananiadou, and Hideki Mima. 2000. Automatic Recognition of Multi-Word Terms: the C-value/NC-value Method. Int. Journal on Digital Libraries 3 (2000), 115--130.
[7]
Konrad Gliściński. 2015. Wszystkie Prawa Zastrzeżone. wolnelektury.pl. https://wolnelektury.pl/media/book/pdf/gliscinski-dyskursy-prawa-autorskiego.pdf
[8]
Kuo-Chuan Huang, James Geller, Michael Halper, Yehoshua Perl, and Junchuan Xu. 2009. Using WordNet synonym substitution to enhance UMLS source integration. Artif. Intell. Medicine 46, 2 (2009), 97--109.
[9]
Wojciech Jaworski, Małgorzata Marciniak, and Agnieszka Mykowiecka. 2021. Side Effect Alerts Generation from EHR in Polish. In Computational Science - ICCS 2021, Maciej Paszynski, Dieter Kranzlmüller, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, and Peter M.A. Sloot (Eds.). Springer International Publishing, Cham, 634--647. https://link.springer.com/chapter/10.1007/978-3-030-77967-2_52
[10]
Małgorzata Marciniak and Agnieszka Mykowiecka. 2014. Terminology extraction from medical texts in Polish. Journal of Biomedical Semantics 5 (2014). http://www.jbiomedsem.com/content/5/1/24
[11]
Małgorzata Marciniak, Agnieszka Mykowiecka, and Piotr Rychlik. 2016. TermoPL --- a Flexible Tool for Terminology Extraction. In Proceedings of LREC. ELRA, Portorož, Slovenia, 2278--2284.
[12]
Małgorzata Marciniak, Agnieszka Mykowiecka, and Piotr Rychlik. 2021. Terminology/Keyphrase Extraction for Creation of Book Indexes in Polish. In Linking Theory and Practice of Digital Libraries, Gerd Berget, Mark Michael Hall, Daniel Brenn, and Sanna Kumpulainen (Eds.). Springer International Publishing, Cham, 49--54. https://link.springer.com/chapter/10.1007/978-3-030-86324-1_5
[13]
Goran Nenadic and Sophia Ananiadou. 2006. Mining semantically related terms from biomedical literature. ACM Trans. Asian Lang. Inf. Process. 5, 1 (2006), 22--43.
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- TermoPL: a tool for extracting and clustering domain related terms
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Published In
June 2022
392 pages
ISBN:9781450393454
DOI:10.1145/3529372
- General Chairs:
- Akiko Aizawa,
- Thomas Mandl,
- Zeljko Carevic,
- Program Chairs:
- Annika Hinze,
- Philipp Mayr,
- Philipp Schaer
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Published: 20 June 2022
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JCDL '22: The ACM/IEEE Joint Conference on Digital Libraries in 2022
June 20 - 24, 2022
Cologne, Germany
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Overall Acceptance Rate 415 of 1,482 submissions, 28%
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View all- Xu KFeng YLi QDong ZWei J(2025)Survey on terminology extraction from textsJournal of Big Data10.1186/s40537-025-01077-x12:1Online publication date: 6-Feb-2025
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