Accurately extracting coherent relevant passages using hidden Markov models

Authors:
Jing Jiang;ChengXiang Zhai
Affiliations:
University of Illinois at Urbana-Champaign, Urbana, IL;University of Illinois at Urbana-Champaign, Urbana, IL
Venue:
Proceedings of the 14th ACM international conference on Information and knowledge management
Year:
2005

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Abstract

In this paper, we present a principled method for accurately extracting coherent relevant passages of variable lengths using HMMs. We show that with appropriate parameter estimation, the HMM method outperforms a number of strong baseline methods on two data sets.