Enhancing Web Search with Heterogeneous Semantic Knowledge

  • Rui Huang
  • Zhongzhi Shi
Conference paper

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

Part of the IFIP – The International Federation for Information Processing book series (IFIPAICT, volume 288)
Cite this paper as:
Huang R., Shi Z. (2008) Enhancing Web Search with Heterogeneous Semantic Knowledge. In: Shi Z., Mercier-Laurent E., Leake D. (eds) Intelligent Information Processing IV. IIP 2008. IFIP – The International Federation for Information Processing, vol 288. Springer, Boston, MA


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.


Web search semantic search semantic Web Web 2.0 ontology social annotation 
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Copyright information

© IFIP 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

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