Minimal Interaction Search in Recommender Systems

Branislav Kveton, Shlomo Berkovsky
2015 Proceedings of the 20th International Conference on Intelligent User Interfaces - IUI '15  
While numerous works study algorithms for predicting item ratings in recommender systems, the area of the userrecommender interaction remains largely under-explored. In this work, we look into user interaction with the recommendation list, aiming to devise a method that allows users to discover items of interest in a minimal number of interactions. We propose generalized linear search (GLS), a combination of linear and generalized searches that brings together the benefits of both approaches.
more » ... prove that GLS performs at least as well as generalized search and compare our method to several baselines and heuristics. Our evaluation shows that GLS is liked by the users and achieves the shortest interactions.
doi:10.1145/2678025.2701367 dblp:conf/iui/KvetonB15 fatcat:zjghenv77vdmdbp5o7weua2o6u