Please use this identifier to cite or link to this item: http://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
Source: 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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