160 citations · 1.2k across the 55 of their papers we have counts for
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cs.IR2018
Online Diverse Learning to Rank from Partial-Click Feedback
Prakhar Gupta, Gaurush Hiranandani, Harvineet Singh +3
Learning to rank is an important problem in machine learning and recommender systems. In a recommender system, a user is typically recommended a list of items. Since the user is un…
cs.IR2014★ 3 cited
DUM: Diversity-Weighted Utility Maximization for Recommendations
Azin Ashkan, Branislav Kveton, Shlomo Berkovsky +1
The need for diversification of recommendation lists manifests in a number of recommender systems use cases. However, an increase in diversity may undermine the utility of the reco…