Implicit Preference Labels for Learning Highly Selective Personalized Rankers
Author:
Affiliation:
1. Microsoft, Redmond, WA, USA
2. Microsoft, Cambridge, United Kingdom
3. Microsoft, Redmond, WA, Uae
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2808194.2809464
Reference39 articles.
1. Improving web search ranking by incorporating user behavior information
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2. Personalized Entity Search by Sparse and Scrutable User Profiles;Proceedings of the 2020 Conference on Human Information Interaction and Retrieval;2020-03-14
3. Risk-Sensitive Evaluation and Learning to Rank using Multiple Baselines;Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval;2016-07-07
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