alexa Abstract | Improving Contextual Web Searches Using Shared Documents
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

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Research Article Open Access

Abstract

Nowadays data is available in a single click that is from World Wide Web which is a huge repository of resources. Web search engines have a key role in the discovery of relevant information, but this kind of search is usually performed using keywords and the results into context less results. Result presented to user may contain context irrelevant data. This work is one step towards better understanding of user context from available domain specific resources. The contextualized strategy for information retrieval (IR) can be built around user profile, query expansion and relevance feedback. In this proposed system, new concept called terminology which is good representative of particular domain (or subject) is defined and used to classify resources as relevant or irrelevant (non- relevant). This work focuses on improving results of context sensitive web search engine based on shared resources. Query expansion using shared documents is applied to implement contextual search. These resources are ranked based on query submitted by user which brings most relevant document at the top in hierarchy. From top ranked documents, terms has been weighted to identify most related terms for query expansion. In addition the results of the query engine with and without the contextual information will be evaluated automatically without any interface of user.

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Author(s): Rushali Patil, Pramod Ganjewar

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