• Login
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage StatisticsView Google Analytics Statistics

    Collaborative filtering approach with decision tree technique

    Thumbnail
    View/Open
    200611034.pdf (475.7Kb)
    Date
    2008
    Author
    Srivastava, Anit
    Metadata
    Show full item record
    Abstract
    Rapid advances in data collection and storage technology has enabled organizations (especially e-commerce) to accumulate vast amounts of data. The amount of data kept in computer files and databases is growing at a phenomenal rate because customers are evolving to use e- commerce services. So processing of large number of coustomer’s past purchase records is becoming a new challenge in e-commerce. The primary goal of e-commerce services is to build the systems where customers can get their likely recommended products relevant to their past purchase. We have implemented collaboratives filtering with supervised learning techniques. One of supervised learning techniques is Decision Tree. We have used Decision Tree to cluster similar type of customers according to active customer preferences (or tastes). In our new approach, a collaborative filtering based recommender system will recommended Top-k likely products according to customers preferences (or tastes) by considering past purchase record (or implicit ratings) of its clustered customers. This system will also recommend or predict Top-k likely products to particular customers by considering the cases when clustered customers have given explicit ratings (or votes) to their previously purchased products.
    URI
    http://drsr.daiict.ac.in/handle/123456789/218
    Collections
    • M Tech Dissertations [923]

    Resource Centre copyright © 2006-2017 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     


    Resource Centre copyright © 2006-2017 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV