Publication: Fewer Flops at the Top: Accuracy, Diversity, and Regularization in Two-Class Collaborative Filtering
Fewer Flops at the Top: Accuracy, Diversity, and Regularization in Two-Class Collaborative Filtering
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Paudel, B., Haas, T., & Bernstein, A. (2017, August 31). Fewer Flops at the Top: Accuracy, Diversity, and Regularization in Two-Class Collaborative Filtering. 11th ACM Conference on Recommender Systems RecSys 2017, Como. https://doi.org/10.1145/3109859.3109916
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In most existing recommender systems, implicit or explicit interactions are treated as positive links and all unknown interactions are treated as negative links. The goal is to suggest new links that will be perceived as positive by users. However, as signed social networks and newer content services become common, it is important to distinguish between positive and negative preferences. Even in existing applications, the cost of a negative recommendation could be high when people are looking for new jobs, friends, or places to live.
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- Paudel, Bibek
- Haas, Thilo
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Citations
Paudel, B., Haas, T., & Bernstein, A. (2017, August 31). Fewer Flops at the Top: Accuracy, Diversity, and Regularization in Two-Class Collaborative Filtering. 11th ACM Conference on Recommender Systems RecSys 2017, Como. https://doi.org/10.1145/3109859.3109916
