A multi-dependency language modeling approach to information retrieval

Authors:
Keke Cai;Chun Chen;Jiajun Bu;Guang Qiu;Peng Huang
Affiliations:
College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China;College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China;College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China;College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China;College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China
Venue:
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Year:
2007

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Abstract

This paper presents a multi-dependency language modeling approach to information retrieval. The approach extends the basic KL-divergence retrieval approach by introducing the hybrid dependency structure, which includes syntactic dependency, syntactic proximity dependency and co-occurrence dependency, to describe dependencies between terms. Term and dependency language models are constructed for both document and query. The relevant between a document and a query is then evaluated by using the KL-divergence between their corresponding models. The new dependency retrieval model has been compared with other traditional retrieval models. Experiment results indicate that it produces significant improvements in retrieval effectiveness.