Abstract
Every day we are facing countless texts on various topics. With a growing number of resources, it is getting harder to find valuable content. There is a need for automated tools to evaluate texts and propose new reads based on their similarity to the original one. The paper aims at introducing a method for calculating the semantic distance between two texts. We use well-known morphological tools to disambiguate the meaning and function of each word in the text. Next, we create the similarity matrixes utilizing the weight of WordNet synset relations. Each term can be part of one of three sets, which visualize three levels of semantic distance. While calculating the distance between texts, we consider statistical characteristics that partly use the identification of terms. However, the primary stress is put on the meaning each word brings to the utterance.
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References
Broda, B., Niton, B., Gruszczynski, W., Ogrodniczuk, M.: Measuring readability of polish texts: baseline experiments. In: LREC, vol. 24, pp. 573–580 (2014)
Debowski, Ł., Broda, B., Nitoń, B., Charzyńska, E.: Jasnopis-a program to compute readability of texts in polish based on psycholinguistic research. In: Natural Language Processing and Cognitive Science, p. 51 (2015)
Dziob, A., Piasecki, M., Rudnicka, E.: plwordnet 4.1-a linguistically motivated, corpus-based bilingual resource. In: Fellbaum, C., Vossen, P., Rudnicka, E., Maziarz, M., Piasecki, M. (eds.) Proceedings of the 10th Global WordNet Conference, Wroclaw, Poland, 23–27 July 2019, pp. 353–362. Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław (2019)
Krótkiewicz, M., Wojtkiewicz, K.: Introduction to semantic knowledge base: Linguistic module. In: 2013 6th International Conference on Human System Interactions (HSI), pp. 356–362. IEEE (2013)
Krótkiewicz, Wojtkiewicz: Features for text comparison. In: Pietka, E., Kawa, J. (eds.) Information Technologies in Biomedicine, pp. 468–475. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-68168-7_52
Kedzia, P., Piasecki, M., Orlińska, M.: Word sense disambiguation based on large scale polish CLARIN heterogeneous lexical resources. Cogn. Stud. Cogn. 15, 269–292 (2015)
Maziarz, M., Piasecki, M., Rudnicka, E., Szpakowicz, S., Kedzia, P.: PlWordNet 3.0 - a comprehensive lexical-semantic resource. In: Calzolari, N., Matsumoto, Y., Prasad, R. (eds.) Proceedings of the 26th International Conference on Computational Linguistics: Technical Papers, COLING 2016, Osaka, Japan, 11–16 December 2016, pp. 2259–2268. ACL (2016). http://www.aclweb.org/anthology/C16-1213
Miller, G.A.: WordNet: An Electronic Lexical Database. MIT press (1998)
Piasecki, M., Szpakowicz, S., Broda, B.: A WordNet from the ground up. Oficyna Wydawnicza Politechniki Wroclawskiej, Wroclaw (2009). http://www.dbc.wroc.pl/Content/4220/_Wordnet.pdf
Straková, J., Straka, M., Hajič, J.: Open-source tools for morphology, lemmatization, POS tagging and named entity recognition. In: Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, Baltimore, Maryland, pp. 13–18. Association for Computational Linguistics (June 2014). http://www.aclweb.org/anthology/P/P14/P14-5003.pdf
Walentynowicz, W.: MorphoDiTa-based tagger for polish language (2017). CLARIN-PL digital repository. http://hdl.handle.net/11321/425
Woliński, M.: Morfeusz – a practical tool for the morphological analysis of Polish. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds.) Intelligent Information Processing and Web Mining. Advances in Soft Computing, pp. 503–512. Springer, Heidelberg (2006). https://doi.org/10.1007/3-540-33521-8_55
Woliński, M.: Morfeusz reloaded. In: Calzolari, N., et al. (eds.) Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014, Reykjavík, Iceland, pp. 1106–1111. European Language Resources Association (ELRA) (2014). http://www.lrec-conf.org/proceedings/lrec2014/index.html
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Wojtkiewicz, K., Kawa, M. (2021). Estimating Semantics Distance of Texts Based on Used Terms Analysis. In: Nguyen, N.T., Iliadis, L., Maglogiannis, I., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science(), vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_50
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DOI: https://doi.org/10.1007/978-3-030-88081-1_50
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