Corpus ID: 57189422

Loss Aversion in Recommender Systems: Utilizing Negative User Preference to Improve Recommendation Quality

@article{Paudel2018LossAI,
  title={Loss Aversion in Recommender Systems: Utilizing Negative User Preference to Improve Recommendation Quality},
  author={Bibek Paudel and Sandro Luck and A. Bernstein},
  journal={ArXiv},
  year={2018},
  volume={abs/1812.11422}
}

Bibek Paudel, Sandro Luck, A. Bernstein

Published 2018

Computer Science, Mathematics

ArXiv

Negative user preference is an important context that is not sufficiently utilized by many existing recommender systems. This context is especially useful in scenarios where the cost of negative items is high for the users. In this work, we describe a new recommender algorithm that explicitly models negative user preferences in order to recommend more positive items at the top of recommendation-lists. We build upon existing machine-learning model to incorporate the contextual information… CONTINUE READING

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