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Web Search Personalization Using Semantic Similarity Measure

  • Sunny SharmaEmail author
  • Vijay Rana
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 597)

Abstract

Web search personalization is the process of providing personalized results to the user for his query. In this paper, we present a relevance model to personalize search results which is based on query personalization. The user query is directly matched to the keywords of the user profile, and the original query is altered according to the keywords which is more likely similar or related according to the similarity measure. By finding the similarity between the user original query and user profile, a linear combination of preference space is generated at run-time to determine more accurately which pages are truly the most important with respect to the modified query. A heuristic algorithm is used to maintain the user profile based on the ongoing behavior. Our experiments prove that retrieving the search results based on query modification is effective in providing the personalized results to the user.

Keywords

Web search personalization Query modification Semantic similarity Semantic annotations 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer ApplicationsChandigarh UniversityMohaliIndia
  2. 2.Department of Computer ApplicationsSBBS UniversityKhialaIndia

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