On Including the User Dynamic in Learning to Rank
Author:
Affiliation:
1. University of Padua, Padua, Italy
2. ISTI-CNR, Pisa, Italy
Funder
EC H2020 Program
SID 2016
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3077136.3080714
Reference20 articles.
1. Improving web search ranking by incorporating user behavior information
2. A taxonomy of web search
3. Learning to rank using gradient descent
4. Quality versus efficiency in document scoring with learning-to-rank models
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