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A Re-ranking Approach Personalized Web Search Results by Using Privacy Protection

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Book cover Information Systems Design and Intelligent Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 434))

Abstract

Various search services quality on the Internet can be improved by personalized web search. Users face sort of dissatisfaction when the results fetched by search engines are not related to the query they have asked for. This irrelevance result is retrieved huge based on the enormous variety of consumers’ perspective and backgrounds, as well as the ambiguity of the contents. However, evidences show that the user’s private information which they search has become public due to the proliferation of Personalized Web Search. The proposed framework RPS implement re-ranking technique, which adaptively make simpler user profiles by queries while respecting the consumer particular constraints of privacy. The great challenge in personalized web search is Privacy protection. To increase the efficiency and accuracy of web search privacy we use Greedy IL algorithm, i.e. GreedyDP and GreedyIL, for runtime generalization. Experiment assessment results show that the privacy-preserving personalized framework and re-ranking approach is highly effective and accurate enough for user profiling privacy personalization on the web search.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Hyderabad, India

    Vijayalakshmi Kakulapati

  2. Department of Computer Science and Engineering, CMRIT, Hyderabad, India

    Sunitha Devi Bigul

Authors
  1. Vijayalakshmi Kakulapati
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  2. Sunitha Devi Bigul
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Corresponding author

Correspondence to Vijayalakshmi Kakulapati .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

  2. Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  3. University of Hyderabad, Hyderabad, India

    Siba K. Udgata

  4. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

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Kakulapati, V., Bigul, S.D. (2016). A Re-ranking Approach Personalized Web Search Results by Using Privacy Protection. In: Satapathy, S.C., Mandal, J.K., Udgata, S.K., Bhateja, V. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 434. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2752-6_7

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  • DOI: https://doi.org/10.1007/978-81-322-2752-6_7

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2750-2

  • Online ISBN: 978-81-322-2752-6

  • eBook Packages: EngineeringEngineering (R0)

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