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An architectural design for effective information retrieval in semantic web |
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| Affiliation: | 1. Madurai Kamaraj University, Madurai 625 021, India;2. Sri Meenakshi Govt. Arts College for Women(A), Madurai 625 002, India;1. Department of Mathematics, Indian Institute of Technology Kharagpur, Kharagpur 721 302, India;2. Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad 500 032, India;1. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, PR China;2. Technology Center of Software Engineering, Institute of Software, Chinese Academy of Sciences, Beijing 100190, PR China;1. Centre of Image and Signal Processing, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia;2. School of Computing, National University of Singapore, Singapore;1. University of Belgrade, Technical Faculty in Bor, VJ 12, Bor, Serbia;2. University of Belgrade, Faculty of Mining and Geology, Djusina 7, Belgrade, Serbia;1. Faculty of Engineering, University of Kragujevac, Serbia;2. Clinic of Urology and Nephrology, Kragujevac, Serbia;3. Military Medical Academy, Belgrade, Serbia |
| Abstract: | The current web IR system retrieves relevant information only based on the keywords which is inadequate for that vast amount of data. It provides limited capabilities to capture the concepts of the user needs and the relation between the keywords. These limitations lead to the idea of the user conceptual search which includes concepts and meanings. This study deals with the Semantic Based Information Retrieval System for a semantic web search and presented with an improved algorithm to retrieve the information in a more efficient way.This architecture takes as input a list of plain keywords provided by the user and the query is converted into semantic query. This conversion is carried out with the help of the domain concepts of the pre-existing domain ontologies and a third party thesaurus and discover semantic relationship between them in runtime. The relevant information for the semantic query is retrieved and ranked according to the relevancy with the help of an improved algorithm. The performance analysis shows that the proposed system can improve the accuracy and effectiveness for retrieving relevant web documents compared to the existing systems. |
| Keywords: | Information retrieval Semantic web Semantic search Ontology Semantic query |
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