A supervised active learning framework for recommender systems based on decision trees

    User Model. User-Adapt. Interact., pp. 39-64, 2015.

    Cited by: 14|Bibtex|10|
    EI
    Keywords:
    Active learningRecommender systemsCold-start problemMatrix factorization

    Abstract:

    A key challenge in recommender systems is how to profile new users. A well-known solution for this problem is to ask new users to rate a few items to reveal their preferences and to use active learning to find optimally informative items. Compared to the application of active learning in classification (regression), active learning in rec...More
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