TY - GEN
T1 - Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows
AU - Song, Dawei
AU - Huang, Qiang
AU - Rüger, Stefan
AU - Bruza, Peter
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
KW - Association rule
KW - Document segmentation
KW - Query expansion
KW - Term relationship
UR - http://www.scopus.com/inward/record.url?scp=41849092634&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-78646-7_31
DO - 10.1007/978-3-540-78646-7_31
M3 - Conference contribution
AN - SCOPUS:41849092634
SN - 3540786457
SN - 9783540786450
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 334
EP - 345
BT - Advances in Information Retrieval - 30th European Conference on IR Research, ECIR 2008, Proceedings
T2 - 30th Annual European Conference on Information Retrieval, ECIR 2008
Y2 - 30 March 2008 through 3 April 2008
ER -