Zhang, Peng; Song, Dawei; Zhao, Xiaozhao and Hou, Yuexian
(2010).
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| URL: | http://link.springer.com/chapter/10.1007%2F978-3-6... |
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| DOI (Digital Object Identifier) Link: | https://doi.org/10.1007/978-3-642-17187-1_50 |
| Google Scholar: | Look up in Google Scholar |
Abstract
In pseudo relevance feedback (PRF), the document weight which indicates how important a document is for the PRF model, plays a key role. In this paper, we investigate the smoothness issue of the document weights in PRF. The term smoothness means that the document weights decrease smoothly (i.e. gradually) along the document ranking list, and the weights are smooth (i.e. similar) within topically similar documents. We postulate that a reasonably smooth document- weighting function can benefit the PRF performance. This hypothesis is tested under a typical PRF model, namely the Relevance Model (RM). We propose a two-step document weight smoothing method, the different instantiations of which have different effects on weight smoothing. Ex- periments on three TREC collections show that the instantiated methods with better smoothing effects generally lead to better PRF performance. In addition, the proposed method can significantly improve the RM’s performance and outperform various alternative methods which can also be used to smooth the document weights.
| Item Type: | Conference or Workshop Item |
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| Copyright Holders: | 2010 Springer-Verlag |
| ISSN: | 0302-9743 |
| Extra Information: | Information Retrieval Technology
6th Asia Information Retrieval Societies Conference, AIRS 2010, Taipei, Taiwan, December 1-3, 2010. Proceedings Editors:Pu-Jen Cheng, Min-Yen Kan, Wai Lam, Preslav Nakov Lecture Notes in Computer Science, 6458 ISBN: 978-3-642-17186-4 (Print) ISBN: 978-3-642-17187-1 (Online) pp.527-538 |
| Keywords: | pseudo relevance feedback; document weight smoothness; query language model; relevance model |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Related URLs: | |
| Item ID: | 35117 |
| Depositing User: | Dawei Song |
| Date Deposited: | 31 Oct 2012 15:34 |
| Last Modified: | 10 Dec 2018 05:17 |
| URI: | http://oro.open.ac.uk/id/eprint/35117 |
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