Song, Dawei; Huang, Qiang; Rüger, Stefan and Bruza, Peter
(2008).
| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1007/978-3-540-78646-7_31 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.
| Item Type: | Conference Item |
|---|---|
| Copyright Holders: | 2008 Springer-Verlag |
| ISSN: | 0302-9743 |
| Academic Unit/Department: | Mathematics, Computing and Technology > Computing Knowledge Media Institute |
| Item ID: | 11960 |
| Depositing User: | Users 8580 not found. |
| Date Deposited: | 08 Oct 2008 13:19 |
| Last Modified: | 22 Oct 2012 10:49 |
| URI: | http://oro.open.ac.uk/id/eprint/11960 |
Actions (login may be required)
| View Item | |
| Public: Report issue / request change |