Please use this identifier to cite or link to this item:
|Title:||Other-anaphora resolution in biomedical texts with automatically mined patterns|
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 29, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.