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A vector space model for automatic indexing
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Introduction to Modern Information Retrieval
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Web Semantics: Science, Services and Agents on the World Wide Web
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Web Semantics: Science, Services and Agents on the World Wide Web
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ICMI'06/IJCAI'07 Proceedings of the ICMI 2006 and IJCAI 2007 international conference on Artifical intelligence for human computing
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SemSearch: a search engine for the semantic web
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
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WISM'12 Proceedings of the 2012 international conference on Web Information Systems and Mining
SWSNL: Semantic Web Search Using Natural Language
Expert Systems with Applications: An International Journal
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In this paper, we present an ontology-based information extraction and retrieval system and its application in the soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inferencing and rules. Scalability is achieved by adapting a semantic indexing approach and representing the whole world as small independent models. The system is implemented using the state-of-the-art technologies in Semantic Web and its performance is evaluated against traditional systems as well as the query expansion methods. Furthermore, a detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inferencing. Finally, we show how we use semantic indexing to solve simple structural ambiguities.