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- Title
EXPANDING APPROACH TO INFORMATION RETRIEVAL USING SEMANTIC SIMILARITY ANALYSIS BASED ON WORDNET AND WIKIPEDIA.
- Authors
ZHAO, FENG; FANG, FEI; YAN, FENGWEI; JIN, HAI; ZHANG, QIN
- Abstract
Performance of information retrieval (IR) systems greatly relies on textual keywords and retrieval documents. Inaccurate and incomplete retrieval results are always induced by query drift and ignorance of semantic relationship among terms. Expanding retrieval approach attempts to incorporate expansion terms into original query, such as unexplored words combing from pseudo-relevance feedback (PRF) or relevance feedback documents semantic words extracting from external corpus etc. In this paper a semantic analysis-based query expansion method for information retrieval using WordNet and Wikipedia as corpus are proposed. We derive semantic-related words from human knowledge repositories such as WordNet and Wikipedia, which are combined with words filtered by semantic mining from PRF document. Our approach automatically generates new semantic-based query from original query of IR. Experimental results on TREC datasets and Google search engine show that performance of information retrieval can be significantly improved using proposed method over previous results.
- Subjects
WIKIPEDIA; INFORMATION retrieval; GOOGLE Inc.; SEARCH engines; QUERY (Information retrieval system); FEEDBACK control systems; COMPUTER science
- Publication
International Journal of Software Engineering & Knowledge Engineering, 2012, Vol 22, Issue 2, p305
- ISSN
0218-1940
- Publication type
Article
- DOI
10.1142/S0218194012500088