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Exploring Semantic Characteristics of Socially Constructed Knowledge Repository to Optimize Web Search
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Author(s): Dengya Zhu (Curtin University, Australia)and Heinz Dreher (Curtin University, Australia)
Copyright: 2013
Pages: 22
Source title:
Advancing Information Management through Semantic Web Concepts and Ontologies
Source Author(s)/Editor(s): Patricia Ordóñez de Pablos (Universidad de Oviedo, Spain), Héctor Oscar Nigro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina), Robert D. Tennyson (University of Minnesota, USA), Sandra Elizabeth Gonzalez Cisaro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina)and Waldemar Karwowski (University of Central Florida, USA)
DOI: 10.4018/978-1-4666-2494-8.ch013
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Abstract
Short-term queries preferred by most users often result in a list of Web search results with low precision from a user perspective. The purpose of this research is to improve the relevance of Web search results via search-term disambiguation and ontological filtering of search results based on socially constructed search concepts. A Special Search Browser (SSB) is developed where semantic characteristics of the socially constructed knowledge repository are extracted to form a category-document set. kNN is employed with the extracted category-documents as training data to classify Web results. Users’ selected categories are employed to present the search results. Experimental results based on five experts’ judgments over 250 hits from Yahoo! API demonstrate that utilizing the socially constructed search concepts to categorize and filter search results can improve precision by 23.5%, from Yahoo’s 41.7% to 65.2% of SSB based on the results of five selected ambiguous search-terms.
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