International Conference on Intelligent Information Processing

IIP 2008: Intelligent Information Processing IV pp 92-101

Enhancing Web Search with Heterogeneous Semantic Knowledge

  • Rui Huang
  • Zhongzhi Shi
Conference paper

DOI: 10.1007/978-0-387-87685-6_13

Volume 288 of the book series IFIP – The International Federation for Information Processing (IFIPAICT)

Abstract

This paper explores four kinds of semantic knowledge to improve keyword-based Web search, including thesauruses, categories, ontologies, and social annotations. These heterogeneous semantic knowledge represent meanings of Web information, thus they can be used to improve search results in respect of semantic relevance. Currently, different semantic search paradigms have been developed for different kind of semantic knowledge respectively. However, how to make the most of all heterogeneous semantic knowledge to optimize Web search is still a big challenge in practice. To these ends, this paper proposes an integrated semantic search mechanism to incorporate textual information and keyword search with heterogeneous semantic knowledge and semantic search. Experiments show that the proposed mechanism effectively integrates heterogeneous semantic knowledge to improve Web search.

Keywords

Web searchsemantic searchsemantic WebWeb 2.0ontologysocial annotation
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Copyright information

© International Federation for Information Processing 2008

Authors and Affiliations

  • Rui Huang
    • 1
    • 2
  • Zhongzhi Shi
    • 1
  1. 1.Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijingChina
  2. 2.Graduate University of the Chinese Academy of SciencesBeijingChina