3 Matching Annotations
- Nov 2020
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psyarxiv.com psyarxiv.com
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Bauer, B., Larsen, K. L., Caulfield, N., Elder, D., Jordan, S., & Capron, D. (2020). Review of Best Practice Recommendations for Ensuring High Quality Data with Amazon’s Mechanical Turk. PsyArXiv. https://doi.org/10.31234/osf.io/m78sf
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- Sep 2020
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psyarxiv.com psyarxiv.com
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Yang, Scott Cheng-Hsin, Chirag Rank, Jake Alden Whritner, Olfa Nasraoui, and Patrick Shafto. ‘Unifying Recommendation and Active Learning for Information Filtering and Recommender Systems’. Preprint. PsyArXiv, 25 August 2020. https://doi.org/10.31234/osf.io/jqa83.
Tags
- is:preprint
- experimental approach
- recommender system
- lang:en
- machine learning
- algorithms
- AI
- recommendation accuracy
- information filtering
- artificial intelligence
- parameterized model
- predictive accuracy
- cognitive science
- computer science
- exploration-exploitation tradeoff
- active learning
- Internet
Annotators
URL
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- Aug 2020
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www.nature.com www.nature.com
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Shi, W., Wang, L., & Qin, J. (2020). Extracting user influence from ratings and trust for rating prediction in recommendations. Scientific Reports, 10(1), 13592. https://doi.org/10.1038/s41598-020-70350-1
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