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

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

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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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