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https://scholarbank.nus.edu.sg/handle/10635/42004
DC Field | Value | |
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dc.title | Other-anaphora resolution in biomedical texts with automatically mined patterns | |
dc.contributor.author | Chen, B. | |
dc.contributor.author | Yang, X. | |
dc.contributor.author | Jian, S. | |
dc.contributor.author | Lim, T.C. | |
dc.date.accessioned | 2013-07-04T08:40:59Z | |
dc.date.available | 2013-07-04T08:40:59Z | |
dc.date.issued | 2008 | |
dc.identifier.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. | |
dc.identifier.isbn | 9781905593446 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/42004 | |
dc.description.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. | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.description.sourcetitle | Coling 2008 - 22nd International Conference on Computational Linguistics, Proceedings of the Conference | |
dc.description.volume | 1 | |
dc.description.page | 121-128 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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