Enhancing Web Search with Heterogeneous Semantic Knowledge

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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.