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Keyword

recommendation algorithms

Description: Computational methods that predict and rank items for users based on preferences, behavior, or item characteristics.
OpenAlex ID: keywords/recommendation-algorithms
Social information filtering
1995 · Upendra Shardanand, Pattie Maes · ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) · 2,824
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An Algorithmic Framework for Performing Collaborative Filtering
2017 · Jonathan L. Herlocker, Joseph A. Konstan, et al. · ACM SIGIR Forum · 2,512
Recommender Systems Handbook
2015 · Francesco Ricci, Lior Rokach, et al. · Springer eBooks · 1,554
The Netflix Recommender System
2015 · Carlos A. Gomez-Uribe, Neil Hunt · ACM Transactions on Management Information Systems · 1,414
Recommender systems
2012 · Linyuan Lü, Matúš Medo, et al. · Physics Reports · 997
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Shilling recommender systems for fun and profit
2004 · Shyong K. Lam, John Riedl · International World Wide Web Conference (WWW) · 641
A systematic review and research perspective on recommender systems
2022 · Deepjyoti Roy, Mala Dutta · Journal Of Big Data · 628
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Managing visibility on YouTube through algorithmic gossip
2019 · Sophie Bishop · New Media & Society · 533
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Intelligent tourism recommender systems: A survey
2014 · Joan Borràs, Antonio Moreno, et al. · Expert Systems with Applications · 516
RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
2021 · Wayne Xin Zhao, Shanlei Mu, et al. · Proceedings of the ... ACM International Conference on Information & Knowledge Management · 479
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Recommendation Systems: Algorithms, Challenges, Metrics, and Business Opportunities
2020 · Zeshan Fayyaz, Mahsa Ebrahimian, et al. · Applied Sciences · 428
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A survey of serendipity in recommender systems
2016 · Denis Kotkov, Shuaiqiang Wang, et al. · Knowledge-Based Systems · 334
A collaborative filtering algorithm and evaluation metric that accurately model the user experience
2004 · Matthew R. McLaughlin, Jonathan L. Herlocker · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · 333
Can an Algorithm be Agonistic? Ten Scenes from Life in Calculated Publics
2015 · Kate Crawford · Science Technology & Human Values · 315
Recommender systems in the healthcare domain: state-of-the-art and research issues
2020 · Thi Ngoc Trang Tran, Alexander Felfernig, et al. · Journal of Intelligent Information Systems · 305
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A Comparison of Collaborative-Filtering Recommendation Algorithms for E-commerce
2007 · Zan Huang, Daniel Zeng, et al. · IEEE Intelligent Systems · 299
The triple‐filter bubble: Using agent‐based modelling to test a meta‐theoretical framework for the emergence of filter bubbles and echo chambers
2018 · Daniel Geschke, Jan Lorenz, et al. · British Journal of Social Psychology · 271
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Constraint-based recommender systems
2008 · A. Felfernig, R. Burke · International Conference on Electronic Commerce · 264
Measuring the Business Value of Recommender Systems
2019 · Dietmar Jannach, Michael Jugovac · ACM Transactions on Management Information Systems · 260
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Recommender Systems Leveraging Multimedia Content
2020 · Yashar Deldjoo, Markus Schedl, et al. · ACM Computing Surveys · 258
Beyond Recommender Systems: Helping People Help Each Other
2001 · Loren Terveen, Will Hill · 250
Network-Based Methods for Prediction of Drug-Target Interactions
2018 · Zengrui Wu, Weihua Li, et al. · Frontiers in Pharmacology · 237
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Multi-Criteria Recommender Systems
2015 · Gediminas Adomavicius, YoungOk Kwon · Springer eBooks · 219
The Future of Personalization at News Websites
2012 · Neil Thurman, Steve Schifferes · Journalism Studies · 219
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Researching YouTube
2018 · Jane Arthurs, Sophia Drakopoulou, et al. · Convergence The International Journal of Research into New Media Technologies · 211
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Works count: 4,972
Citation count: 38,900
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