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|Title:||Automatic relation extraction with model order selection and discriminative label identification||Authors:||Chen, J.
|Issue Date:||2005||Citation:||Chen, J.,Ji, D.,Tan, C.L.,Niu, Z. (2005). Automatic relation extraction with model order selection and discriminative label identification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3651 LNAI : 390-401. ScholarBank@NUS Repository.||Abstract:||In this paper, we study the problem of unsupervised relation extraction based on model order identification and discriminative feature analysis. The model order identification is achieved by stability-based clustering and used to infer the number of the relation types between entity pairs automatically. The discriminative feature analysis is used to find discriminative feature words to name the relation types. Experiments on ACE corpus show that the method is promising. © Springer-Verlag Berlin Heidelberg 2005.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/41231||ISBN:||3540291725||ISSN:||03029743|
|Appears in Collections:||Staff Publications|
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