Context based Indexing in Search Engines using Ontology

Abstract

Indexing in search engines has been an active area of current researches. The main aim of search engines is to provide most relevant documents to the users in minimum possible time. So granting efficient and fast accesses to the index is a major issue for performances of Web Search Engines. Indexing is performed on the web pages after they have been gathered into a repository by the crawler. The existing architecture of search engine shows that the index is built on the basis of the terms of the document and consists of an array of the posting lists where each posting list is associated with a term and contains the term as well as the identifiers of the documents containing the term. The current information retrieval systems use terms to describe documents and search engines. This paper proposes an indexing structure in which index is built on the basis of context of the document rather than on the terms basis using ontology. The ontology-based collection selection method presented in this paper uses context to describe collections and search engines. The context of the documents being collected by the crawler in the repository is being extracted by the indexer using the context repository, thesaurus and ontology repository and then documents are indexed according to their respective context. General Terms Algorithm, Theory, Performance.