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2009 WRI World Congress on Computer Science and Information Engineering
Application of Symbol Feature-Based HMM in Web Information Extraction
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
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.
Index Terms:
Keywords Hidden Markov Model(HMM), Symbol feature, Information Extraction
Citation:
Ma Yongjin, Jin Bingyao, "Application of Symbol Feature-Based HMM in Web Information Extraction," csie, vol. 4, pp.173-177, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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