Front Inner Page - Volume 3 No.5 October 2016

  • » Back to Index

  • Title

    :

    Web Personalization Recommendation System Based on Clustering and Association Rule

    Authors

    :

    S R Lomate

    Keywords

    :

    Web personalization recommendation system; association rules; Clustering, K-medoids, filtering, web mining

    Issue Date

    :

    October 2016

    Abstract

    :

    Nowadays, the quality and getting amount of results are the major problems faced in the web search. The showing results may irritate a user and consuming the precious time. In order to overcome this drawbacks, this paper proposes a new personalized recommendation system integrating clustering and association rule technique. It also overcomes the drawbacks of traditional recommendation system. The main objective of this paper is, to provide required information for the users clearly. A web recommender system is a web-based interactive software agent. For the purpose of enabling and personalizing user’s online experience, the WRS is to predict user preferences from data and access data by providing list of recommendation items. This system improves the recommendation quality of system and save time of recommendation process.

    Page(s)

    :

    1-5

    ISSN

    :

    2347- 4734

    Source

    :

    Vol. 3, No.5, October 2016

    Download

    :


  • » Back index