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https://scholarbank.nus.edu.sg/handle/10635/42004
Title: | Other-anaphora resolution in biomedical texts with automatically mined patterns | Authors: | Chen, B. Yang, X. Jian, S. Lim, T.C. |
Issue Date: | 2008 | Citation: | Chen, B.,Yang, X.,Jian, S.,Lim, T.C. (2008). Other-anaphora resolution in biomedical texts with automatically mined patterns. Coling 2008 - 22nd International Conference on Computational Linguistics, Proceedings of the Conference 1 : 121-128. ScholarBank@NUS Repository. | Abstract: | This paper proposes an other-anaphora resolution approach in bio-medical texts. It utilizes automatically mined patterns to discover the semantic relation between an anaphor and a candidate antecedent. The knowledge from lexical patterns is incorporated in a machine learning framework to perform anaphora resolution. The experiments show that machine learning approach combined with the auto-mined knowledge is effective for other-anaphora resolution in the biomedical domain. Our system with auto-mined patterns gives an accuracy of 56.5%., yielding 16.2% improvement against the baseline system without pattern features, and 9% improvement against the system using manually designed patterns. © 2008 Licensed under the Creative Commons. | Source Title: | Coling 2008 - 22nd International Conference on Computational Linguistics, Proceedings of the Conference | URI: | http://scholarbank.nus.edu.sg/handle/10635/42004 | ISBN: | 9781905593446 |
Appears in Collections: | Staff Publications |
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