Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows.
Song, Dawei; Huang, Qiang; Rüger, Stefan; Bruza, Peter
Ryen W. White
This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term re- lationships in query language modeling, which takes into account terms implicitly associated with diÂ®erent subsets of query terms. Existing ap- proaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associa- tions and also suÂ®er from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback docu- ments that are segmented into variable length chunks via multiple sliding windows of diÂ®erent sizes. Extensive experiments have been conducted on various TREC collections and our approach signiÂ¯cantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.
|Start Date||Mar 30, 2008|
|Publication Date||Dec 31, 2008|
|Publisher||Springer (part of Springer Nature)|
|Series Title||Lecture notes in computer science|
|Institution Citation||SONG, D., HUANG, Q., RUGER, S. and BRUZA, P. 2008. Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows. In Macdonald, C., Ounis, I., Plachouras, V., Ruthven I. and White, R.W. (eds.) Advances in information retrieval: proceedings of the 30th European conference on information retrieval (IR) research (ECIR 2008), 30 March - 3 April 2008, Glasgow, UK. Lecture notes in computer science, 4956. Berlin: Springer [online], pages 334-345. Available from: https://doi.org/10.1007/978-3-540-78646-7_31|
|Keywords||Association rule; Term relationship; Query expansion; Document segmentation|
SONG 2008 Facilitating query decomposition
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