Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/77963
Title: A machine learning approach to identification and resolution of one-anaphora
Authors: Ng, H.T. 
Zhou, Y.
Dale, R.
Gardiner, M.
Issue Date: 2005
Source: Ng, H.T.,Zhou, Y.,Dale, R.,Gardiner, M. (2005). A machine learning approach to identification and resolution of one-anaphora. IJCAI International Joint Conference on Artificial Intelligence : 1105-1110. ScholarBank@NUS Repository.
Abstract: We present a machine learning approach to identifying and resolving one-anaphora. In this approach, the system first learns to distinguish different uses of instances of the word one; in the second stage, the antecedents of those instances of one that are classified as anaphoric are then determined. We evaluated our approach on written texts drawn from the informative domains of the British National Corpus (BNC), and achieved encouraging results. To our knowledge, this is the first learningbased system for the identification and resolution of one-anaphora.
Source Title: IJCAI International Joint Conference on Artificial Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/77963
ISSN: 10450823
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

22
checked on Feb 23, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.