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.

DOI: https://doi.org/10.1145/1458082.1458310

URL: http://dl.acm.org/citation.cfm?id=1458310

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 base- lines in terms of both effectiveness and robustness.

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About

• Item ORO ID
• 35333
• Item Type
• Conference or Workshop Item
• 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
  pp.1417-1418
• Keywords
• Information retrieval, latent variable model, hidden Markov model
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
  Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
• Copyright Holders
• © 2008 The Authors
• Related URLs
• • http://www.cikm2008.org/(Other)
• Depositing User
• Dawei Song