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

Huang, Qiang and Song, Dawei (2008). A latent variable model for query expansion using the hidden Markov model. In: ACM 17th Conference on Information and Knowledge Management (CIKM2008), 26-30 Oct 2008, Napa Valley, CA, USA.

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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 base- lines in terms of both effectiveness and robustness.

Item Type: Conference Item
Copyright Holders: 2008 The Authors
Extra Information: CIKM '08
Proceedings of the 17th ACM Conference on Information and Knowledge Management
ACM, New York, NY, 2008
ISBN: 978-1-59593-991-3
Keywords: Information retrieval, latent variable model, hidden Markov model
Academic Unit/Department: Knowledge Media Institute
Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
Related URLs:
Item ID: 35333
Depositing User: Dawei Song
Date Deposited: 15 Nov 2012 09:49
Last Modified: 25 Feb 2016 00:40
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