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Minimal Interaction Search in Recommender Systems
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.
doi:10.1145/2678025.2701367
dblp:conf/iui/KvetonB15
fatcat:zjghenv77vdmdbp5o7weua2o6u