Topic-based website feature analysis for enterprise search from the web

Authors:
Baoli Dong;Huimei Liu;Zhaoyong Hou;Xizhe Liu
Affiliations:
Department of Mechanical Engeering, Taiyuan University of Science and Technology, Taiyuan, China;School of Science, Taiyuan University of Technology, Taiyuan, China;School of Science, Taiyuan University of Technology, Taiyuan, China;Institute of Manufacturing Engineering, Zhejiang University, Hangzhou, China
Venue:
WISE'06 Proceedings of the 7th international conference on Web Information Systems
Year:
2006

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Abstract

Efficient and accurate enterprise search is a challenging and important problem for specified resources available on the web. Domain-specific enterprise websites are similar in the topic structures and textual contents. Considering the semantic information of website content terms, a novel website feature vector modelling method representing website topic were proposed on the basis of vector space model. The feature vector elements integrated textual semantic information about topic content and structure information through different semantic terms and weighting schema respectively. The contrast recognition performances demonstrate that this feature analysis approach to website topic gives full potentials for specific enterprise web search.