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Application of Genetic Algorithm and Back Propagation Neural Network for Effective Personalize Web Search-Based on Clustered Query Sessions

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  • Suruchi Chawla

    (Shaheed Rajguru College of Applied Science for Women, University of Delhi, Delhi, India)

Abstract

In this paper novel method is proposed using hybrid of Genetic Algorithm (GA) and Back Propagation (BP) Artificial Neural Network (ANN) for learning of classification of user queries to cluster for effective Personalized Web Search. The GA- BP ANN has been trained offline for classification of input queries and user query session profiles to a specific cluster based on clustered web query sessions. Thus during online web search, trained GA –BP ANN is used for classification of new user queries to a cluster and the selected cluster is used for web page recommendations. This process of classification and recommendations continues till search is effectively personalized to the information need of the user. Experiment was conducted on the data set of web user query sessions to evaluate the effectiveness of Personalized Web Search using GA optimized BP ANN and the results confirm the improvement in the precision of search results.

Suggested Citation

  • Suruchi Chawla, 2016. "Application of Genetic Algorithm and Back Propagation Neural Network for Effective Personalize Web Search-Based on Clustered Query Sessions," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 7(1), pages 33-49, January.
    • Handle: RePEc:igg:jaec00:v:7:y:2016:i:1:p:33-49
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    Cited by:

    1. Tijeni Delleji & Feten Slimeni & Hedi Fekih & Achref Jarray & Wadi Boughanmi & Abdelaziz Kallel & Zied Chtourou, 2022. "An Upgraded-YOLO with Object Augmentation: Mini-UAV Detection Under Low-Visibility Conditions by Improving Deep Neural Networks," SN Operations Research Forum, Springer, vol. 3(4), pages 1-27, December.

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