Huang, Qiang; Song, Dawei and Rüger, Stefan
(2008).
| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1007/978-3-540-78646-7_54 |
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| Google Scholar: | Look up in Google Scholar |
Abstract
In document retrieval using pseudo relevance feedback, after initial ranking, a fixed number of top-ranked documents are selected as feedback to build a new expansion query model. However, very little attention has been paid to an intuitive but critical fact that the retrieval performance for different queries is sensitive to the selection of different numbers of feedback documents. In this paper, we explore two approaches to incorporate the factor of query-specific feedback document selection in an automatic way. The first is to determine the “optimal” number of feedback documents with respect to a query by adopting the clarity score and cumulative gain. The other approach is that, instead of capturing the optimal number, we hope to weaken the effect of the numbers of feedback document, i.e., to improve the robustness of the pseudo relevance feedback process, by a mixture model. Our experimental results show that both approaches improve the overall retrieval performance.
| Item Type: | Conference Item |
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| Copyright Holders: | 2008 Springer-Verlag |
| Academic Unit/Department: | Knowledge Media Institute Mathematics, Computing and Technology > Computing |
| Item ID: | 11961 |
| Depositing User: | Users 8580 not found. |
| Date Deposited: | 08 Oct 2008 13:54 |
| Last Modified: | 22 Oct 2012 10:49 |
| URI: | http://oro.open.ac.uk/id/eprint/11961 |
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