Abstract
We propose a novel machine learning approach to the task of identifying definitions in Polish documents. Specifics of the problem domain and characteristics of the available dataset have been taken into consideration, by carefully choosing and adapting a classification method to highly imbalanced and noisy data. We evaluate the performance of a Random Forest-based classifier in extracting definitional sentences from natural language text and give a comparison with previous work.
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References
Breiman, L.: Random forests. Machine Learning 45, 5–32 (2001)
Chen, C., Liaw, A., Breiman, L.: Using random forest to learn imbalanced data. Technical Report 666, University of California, Berkeley (2004), http://www.stat.berkeley.edu/tech-reports/666.pdf
Degórski, Ł, Marcińczuk, M., Przepiórkowski, A.: Definition extraction using a sequential combination of baseline grammars and machine learning classifiers. In: Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC 2008). ELRA, Forthcoming (2008)
Fahmi, I., Bouma, G.: Learning to identify definitions using syntactic features. In: Proceedings of the EACL 2006 workshop on Learning Structured Information in Natural Language Applications (2006)
Kingsbury, P., Palmer, M.: From TreeBank to PropBank. In: Proceedings of the Third International Conference on Language Resources and Evaluation, LREC 2002, pp. 1989–1993. ELRA, Las Palmas (2002)
Klavans, J.L., Muresan, S.: DEFINDER: Rule-based methods for the extraction of medical terminology and their associated definitions from on-line text. In: Proceedings of the Annual Fall Symposium of the American Medical Informatics Association (2000)
Klavans, J.L., Muresan, S.: Evaluation of the DEFINDER system for fully automatic glossary construction. In: Proceedings of AMIA Symposium (2001)
Lin, D., Wu, D. (eds.): Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing (EMNLP 2004). ACL, Barcelona (2004)
Malaisé, V., Zweigenbaum, P., Bachimont, B.: Detecting semantic relations between terms in definitions. In: Ananadiou, S., Zweigenbaum, P. (eds.) COLING 2004 CompuTerm 2004: 3rd International Workshop on Computational Terminology, Geneva, Switzerland, pp. 55–62 (2004)
Miliaraki, S., Androutsopoulos, I.: Learning to identify single-snippet answers to definition questions. In: Proceedings of COLING 2004, Geneva, Switzerland, pp. 1360–1366 (2004)
Nielsen, R.D., Pradhan, S.: In: Lin,, Wu (eds.) Mixing weak learners in semantic parsing, pp. 80–87 (2004)
Pearson, J.: The expression of definitions in specialised texts: a corpus-based analysis. In: Gellerstam, M., Järborg, J., Malmgren, S.G., Norén, K., Rogström, L., Papmehl, C. (eds.) Proceedings of the Seventh Euralex International Congress, Göteborg, pp. 817–824 (1996)
Przepiórkowski, A., Degórski, Ł, Wójtowicz, B.: On the evaluation of Polish definition extraction grammars. In: Vetulani, Z. (ed.) Proceedings of the 3rd Language & Technology Conference, Poznań, Poland, pp. 473–477 (2007a)
Przepiórkowski, A., Degórski, Ł, Spousta, M., Simov, K., Osenova, P., Lemnitzer, L., Kuboň, V., Wójtowicz, B.: Towards the automatic extraction of definitions in Slavic. In: Piskorski, J., Pouliquen, B., Steinberger, R., Tanev, H. (eds.) Proceedings of the Workshop on Balto-Slavonic Natural Language Processing at ACL 2007, Prague, pp. 43–50 (2007b)
Przepiórkowski, A., Marcińczuk, M., Degórski, Ł.: Dealing with small, noisy and imbalanced data: Machine learning or manual grammars? In: Sojka, P., Kopeček, I., Pala, K. (eds.) Text, Speech and Dialogue: 9th International Conference (TSD 2008), Brno, Czech Republic, September 2008. LNCS (LNAI). Springer, Berlin (2008)
Storrer, A., Wellinghoff, S.: Automated detection and annotation of term definitions in German text corpora. In: Proceedings of the Fifth International Conference on Language Resources and Evaluation, LREC 2006, ELRA, Genoa (2006)
Walter, S., Pinkal, M.: Automatic extraction of definitions from German court decisions. In: Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Sydney, Australia, pp. 20–28 (2006)
Xu, P., Jelinek, F.: In: Lin,, Wu (eds.) Random forests in language modeling, pp. 325–332 (2004)
Xu, P., Jelinek, F.: Random forests and the data sparseness problem in language modeling. Computer Speech and Language 21(1), 105–152 (2007)
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Kobyliński, Ł., Przepiórkowski, A. (2008). Definition Extraction with Balanced Random Forests. In: Nordström, B., Ranta, A. (eds) Advances in Natural Language Processing. GoTAL 2008. Lecture Notes in Computer Science(), vol 5221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85287-2_23
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DOI: https://doi.org/10.1007/978-3-540-85287-2_23
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