A Framework for Context Ontology Driven Indexing, Ranking and Search in Search Engines

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Parul Gupta
Dr. A.K. Sharma


The size of the publicly indexable World Wide Web (WWW) has probably surpassed 14.3 billion documents and as yet growth shows no sign of leveling off. As more information becomes available on the Web it is more difficult to provide effective search services for Internet users. This paper integrates the proposed architecture for hierarchical clustering based indexing, multilevel indexing, context based index which further leads to the creation of ranked context based index using ontology. Context-ontology is a shared vocabulary to share context information in a pervasive computing domain and include machine-interpretable definitions of basic concepts in the domain and relations among them. Further ontology driven conjunctive query expansion based on mining user logs and architecture for relevant searching of web documents using data mining techniques such as clustering and association rules has been presented. Context Ontology has also been applied to ranking of the search results. An attempt has been made to measure the performance and compare the results of the prevailing approach and the new approach.


Keywords: Context Ontology, multilevel indexing, query expansion, clustering, context repository


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