Conceptual Query Expansion Model for Web Information Retrieval
Olufade F. W. Onifade
Department of Computer Science, University of Ibadan, Nigeria
Ayodeji O. J. Ibitoye *
Department of Computer Science and Information Technology, Bowen University, Nigeria
*Author to whom correspondence should be addressed.
Abstract
The process of retrieving relevant documents from user query is to begin with the clustering of documents with high semantic similarities between terms, and lower inner noise values. Here, the research extends normal keywords document clustering techniques in automatic thesaurus construction to building a Concept Based Thesaurus Network. The applied concept matching algorithm uses the Multi-Fuzzy Concept Network to generate sub clustered documents with relative degree of relationship across the clustered document. The proposed system achieved a higher cohesion rate between concepts and lower entropy rate in document. Also, a concise and relevant potential retrieved document were better ranked when compared with other existing document clustering techniques.
Keywords: Concept based thesaurus network, concepts, document clustering, fuzzy concept network, concept based document clustering