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Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
ISBN: 978-0-7695-3507-4
pp: 173-177
This paper proposes a symbol feature-based Hidden Markov Model (HMM). Each state in the model is expressed by some symbol features, and is described by feature lists that draw from regular expressions and text inference; based on which, we use Veterbi Algorithm to extract the information from scientific researchers’ homepages. It works well although there is great information redundancy.
Keywords Hidden Markov Model(HMM), Symbol feature, Information Extraction

M. Yongjin and J. Bingyao, "Application of Symbol Feature-Based HMM in Web Information Extraction," 2009 WRI World Congress on Computer Science and Information Engineering, CSIE(CSIE), Los Angeles, CA, 2009, pp. 173-177.
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