A latent variable model for query expansion using the hidden markov model

Authors:
Qiang Huang;Dawei Song
Affiliations:
The Open University, Milton Keynes, United Kingdom;The Open University, Milton Keynes, United Kingdom
Venue:
Proceedings of the 17th ACM conference on Information and knowledge management
Year:
2008

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Abstract

We propose a novel probabilistic method based on the Hidden Markov Model(HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed LVM, the combinations of query terms are viewed as the latent variables and the segmented chunks from the feedback documents are used as the observations given these latent variables. Our extensive experiments shows that our method significantly outperforms a number of strong baselines in terms of both effectiveness and robustness.