A supervised active learning framework for recommender systems based on decision trees
User Model. User-Adapt. Interact., pp. 39-64, 2015.
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
Get fulltext within 24h
Full Text (Upload PDF)
PPT (Upload PPT)