Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.98
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
Ma Yongjin, Jin Bingyao, "Application of Symbol Feature-Based HMM in Web Information Extraction", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 173-177, doi:10.1109/CSIE.2009.98