Active learning is a learning task where the learner actively selects the instances for which it wants to know the target values. In the context of recommender systems, an example would be the selection of a list of items that a user should rate in order to get improved recommendations.
- N. Rubens, D. Kaplan, M. Sugiyama. Recommender Systems Handbook: Active Learning in Recommender Systems (eds. F. Ricci, P.B. Kantor, L. Rokach,B. Shapira). Springer, 2011 , .
- I. Rish and G. Tesauro. Active Collaborative Prediction with Maximum Margin Matrix Factorization, invited paper/talk at Information Theory and Applications (ITA) Workshop, San Diego, Feb 2007.
- Nadav Golbandi, Yehuda Koren, Ronny Lempel: Adaptive Bootstrapping of Recommender Systems Using Decision Trees, WSDM 2011.