Abstract
In this paper, we propose a new unsupervised method of extracting events from biomedical literature, which uses the score measures of events and patterns having reciprocal effects on each other. We, first, generate candidate events by performing linguistic preprocessing and utilizing basic event pattern information, and then extract reliable events based on the event score which is estimated by using co-occurrence information of candidate event’s arguments and pattern score. Unlike the previous approaches, the proposed approach does not require a huge number of rules and manually constructed training corpora.
Experimental results on GENIA corpora show that the proposed method can achieve high recall (69.7%) as well as high precision (90.3%).
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References
Douglas, E.: Appelt: Introduction to information extraction. Artificial Intelligence Communications 12(3), 161–172 (1999)
Proux, D., et al.: A pragmatic information extraction strategy for gathering data on genetic interactions. ISMB 8, 279–285 (2000)
Ono, T., et al.: Automated extraction of information on protein-protein interactions from the biological literature. Bioinformatics 17(2), 155–161 (2001)
Grishman, R.: Information Extraction: Techniques and Challenges. In: Proceedings of the Seventh Message Understanding Conference (MUC-7), Columbia (1998)
Pustejovsky, J., et al.: Medstract: Creating Large-scale Information Servers for biomedical libraries. In: Proceedings of the Workshop on Natural Language Processing in the Biomedical Domain, pp. 85–92 (2002)
Jenssen, T.-K., et al.: A literature network of human genes for highthroughput analysis of gene expression. Nat. Genet. 28(1), 21–28 (2001)
Hwang, Y.-s., et al.: Weighted Probabilistic Sum Model based on Decision Tree Decomposition for Text Chunking. International Journal of Computer Processing of Oriental Languages 16(1) (2003)
Lee, K.-j., Hwang, Y.-s., Rim, H.-c.: Two-Phase Biomedical NE Recognition based on SVMs. In: Proceedings of the ACL 2003 Workshop on Natural Language Processing in Biomedicine, pp. 33–40 (2003)
Park, K.-m., Hwang, Y.-s., Rim, H.-c.: Grammatical Relation Analysis Using Support Vector Machine in Biotext. In: Proceedings of the 15th Conference of Hangul and Korean Information Processing, pp. 287–292 (2003)
GENIA Corpus 3.0p (2003), http://www-tsujii.is.s.u-tokyo.ac.jp/genia/topics/Corpus/3.0/GENIA3.0p.intro.html
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© 2005 Springer-Verlag Berlin Heidelberg
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Chun, Hw., Hwang, Ys., Rim, HC. (2005). Unsupervised Event Extraction from Biomedical Literature Using Co-occurrence Information and Basic Patterns. In: Su, KY., Tsujii, J., Lee, JH., Kwong, O.Y. (eds) Natural Language Processing – IJCNLP 2004. IJCNLP 2004. Lecture Notes in Computer Science(), vol 3248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30211-7_83
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DOI: https://doi.org/10.1007/978-3-540-30211-7_83
Publisher Name: Springer, Berlin, Heidelberg
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