Recommender Response to Diversity and Popularity Bias in User Profiles

@inproceedings{Channamsetty2017RecommenderRT,
  title={Recommender Response to Diversity and Popularity Bias in User Profiles},
  author={Sushma Channamsetty and Michael D. Ekstrand},
  booktitle={FLAIRS Conference},
  year={2017}
}
Recommender system evaluation usually focuses on the overall effectiveness of the algorithms, either in terms of measurable accuracy or ability to deliver user satisfaction or improve business metrics. When additional factors are considered, such as the diversity or novelty of the recommendations, the focus typically remains on the algorithm’s overall performance. We examine the relationship of the recommender’s output characteristics – accuracy, popularity (as an inverse of novelty), and… Expand
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