Efficient Mining and Recommendation of Extensive Data Through Collaborative Filtering in E-Commerce: A Survey

  • Authors

    • N Naveen
    • S Ganesh Kumar
    2018-04-25
    https://doi.org/10.14419/ijet.v7i2.24.12077
  • E-commerce, Group recommender system (GRS), recommendation based system, User Preferences.

  • Abstract

    E-Commerce is the most widely used technique nowadays. Buying and selling goods on the Internet has been most admired and frequently utilized. The humongous growth of the content available on the internet has made laborious for users to search and utilize information for classifying the products. Recommendation system regarded as the best way to help the customers in buying the related products. (GRS) group recommender system aims at enhancing the customer’s benefits for buying the products. This paper summarizes the fuzzy tree matching, modeling user preference dynamics, web page recommendation, uncertainty analysis for keywords, recommender system application, temporal topic model for friend recommendation, autocratic decision-making system based on (GRS),modeling user recommender, evaluating recommender system and enhancing (GRS).

     

     

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  • How to Cite

    Naveen, N., & Ganesh Kumar, S. (2018). Efficient Mining and Recommendation of Extensive Data Through Collaborative Filtering in E-Commerce: A Survey. International Journal of Engineering & Technology, 7(2.24), 331-335. https://doi.org/10.14419/ijet.v7i2.24.12077

    Received date: 2018-04-24

    Accepted date: 2018-04-24

    Published date: 2018-04-25