• Login
    View Item 
    •   SMARTech Home
    • Undergraduate Research Opportunities Program (UROP)
    • Undergraduate Research Option Theses
    • View Item
    •   SMARTech Home
    • Undergraduate Research Opportunities Program (UROP)
    • Undergraduate Research Option Theses
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Overlapping Clustering of Contextual Bandits with NMF techniques

    Thumbnail
    View/Open
    KWON-UNDERGRADUATERESEARCHOPTIONTHESIS-2017.pdf (188.8Kb)
    Author
    Kwon, Jin Kyoung
    Metadata
    Show full item record
    Abstract
    We introduce a novel approach to recommendation based on item clustering using non-negative matrix factorization (NMF) techniques. We propose a new algorithm, OCB (Overlapping Clustering Bandits), that groups items into latent clusters using online user feedbacks and uses learned clusters to make recommendations. By making recommendation at cluster-level instead of at item-level, the algorithm can overcome scalability issues associated with a large number of items without compensating for long-term reward maximization. Also, by performing online clustering of items, the algorithm can learn latent topics associated with items based on user feedbacks.
    URI
    http://hdl.handle.net/1853/60329
    Collections
    • School of Computer Science Undergraduate Research Option Theses [125]
    • Undergraduate Research Option Theses [631]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    • About
    • Terms of Use
    • Contact Us
    • Emergency Information
    • Legal & Privacy Information
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    • Login
    Georgia Tech

    © Georgia Institute of Technology

    • About
    • Terms of Use
    • Contact Us
    • Emergency Information
    • Legal & Privacy Information
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    • Login
    Georgia Tech

    © Georgia Institute of Technology