Continuous optimization for item selection in collaborative filtering

Kohei Inoue, Kiichi Urahama

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)


    A method is presented for selecting items asked for new users to input their preference rates on those items in recommendation systems based on the collaborative filtering. Optimal item selection is formulated by an integer programming problem and we solve it by using a kind of the Hopfield-network-like scheme for interior point methods.

    Original languageEnglish
    Pages (from-to)1987-1988
    Number of pages2
    JournalIEICE Transactions on Information and Systems
    Issue number7
    Publication statusPublished - Jul 2004

    All Science Journal Classification (ASJC) codes

    • Software
    • Artificial Intelligence
    • Electrical and Electronic Engineering
    • Computer Vision and Pattern Recognition
    • Hardware and Architecture


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