Novel Approach to Query Expansion Using Genetic Algorithm on Clustered Query Sessions for Effective Personalized Web Search

Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
Research has been done based on query expansion to bridge the gap between vocabulary of user search query and documents relevant to user in order to retrieve relevant documents early in search results. In this paper, novel approach is proposed for recommending optimal set of terms for query expansion using genetic algorithm based on clustered query sessions. The genetic algorithm is applied on clustered query sessions for user input queries optimization in order to identify the optimal set of expansion terms relevant to the domain of cluster. The initial input query issued for search on the web is used to select the cluster for recommending the set of terms for query expansion.

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