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|Title:||Word sense disambiguation improves information retrieval||Authors:||Zhong, Z.
|Issue Date:||2012||Citation:||Zhong, Z.,Ng, H.T. (2012). Word sense disambiguation improves information retrieval. 50th Annual Meeting of the Association for Computational Linguistics, ACL 2012 - Proceedings of the Conference 1 : 273-282. ScholarBank@NUS Repository.||Abstract:||Previous research has conflicting conclusions on whether word sense disambiguation (WSD) systems can improve information retrieval (IR) performance. In this paper, we propose a method to estimate sense distributions for short queries. Together with the senses predicted for words in documents, we propose a novel approach to incorporate word senses into the language modeling approach to IR and also exploit the integration of synonym relations. Our experimental results on standard TREC collections show that using the word senses tagged by a supervised WSD system, we obtain significant improvements over a state-of-the-art IR system. © 2012 Association for computational Linguistics.||Source Title:||50th Annual Meeting of the Association for Computational Linguistics, ACL 2012 - Proceedings of the Conference||URI:||http://scholarbank.nus.edu.sg/handle/10635/78433||ISBN:||9781937284244|
|Appears in Collections:||Staff Publications|
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