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Recommendation systems are ubiquitous and impact many domains; they have the potential to influence product consumption, individuals' perceptions of the world, and life-altering decisions.
Algorithms for non-negative matrix factorization
Lee, D. D., and Seung, H. S · 2000
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SciPy: Open source scientific tools for Python, 2001–
Jones, E., Oliphant, T., Peterson, P., et al · 2001
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Principal component analysis
Jolliffe, I · 2002
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Latent Dirichlet allocation
Blei, D. M., Ng, A. Y., and Jordan, M. I · 2003
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Movielens unplugged: experiences with an occasionally connected recommender system
Miller, B. N., Albert, I., Lam, S. K., Konstan, J. A., and Riedl, J · 2003
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GaP: a factor model for discrete data
Canny, J · 2004
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Evaluating collaborative filtering recommender systems
Herlocker, J. L., Konstan, J. A., Terveen, L. G., and Riedl, J. T · 2004
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The long tail: Why the future of business is selling less of more
Anderson, C · 2006
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Leveraging missing ratings to improve online recommendation systems
Ying, Y., Feinberg, F., and Wedel, M · 2006
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Lessons from the netflix prize challenge
Bell, R. M., and Koren, Y · 2007
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The netflix prize
Bennett, J., Lanning, S., et al · 2007
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Trust-aware recommender systems
Massa, P., and Avesani, P · 2007
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Probabilistic matrix factorization
Salakhutdinov, R., and Mnih, A · 2007
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A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem
Ahn, H. J · 2008
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From hits to niches?: or how popular artists can bias music recommendation and discovery
Celma, Ò., and Cano, P · 2008
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Collaborative filtering for implicit feedback datasets
Hu, Y., Koren, Y., and Volinsky, C · 2008
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Factorization meets the neighborhood: A multifaceted collaborative filtering model
Koren, Y · 2008
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The long tail of recommender systems and how to leverage it
Park, Y.-J., and Tuzhilin, A · 2008
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Blockbuster culture’s next rise or fall: The impact of recommender systems on sales diversity
Fleder, D., and Hosanagar, K · 2009
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Controlled experiments on the web: survey and practical guide
Kohavi, R., Longbotham, R., Sommerfield, D., and Henne, R. M · 2009
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Matrix factorization techniques for recommender systems
Koren, Y., Bell, R., and Volinsky, C · 2009
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Collaborative prediction and ranking with non-random missing data
Marlin, B. M., and Zemel, R. S · 2009
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The value of the unpopular: Counteracting the popularity echo-chamber on the web
Treviranus, J., and Hockema, S · 2009
Cited alongside, same era.
The long tail in recommender systems
Celma, Ò · 2010
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Performance of recommender algorithms on top-n recommendation tasks
Cremonesi, P., Koren, Y., and Turrin, R · 2010
Cited alongside, same era.
Collaborative filtering with temporal dynamics
Koren, Y · 2010
Cited alongside, same era.
A contextual-bandit approach to personalized news article recommendation
Li, L., Chu, W., Langford, J., and Schapire, R. E · 2010
Cited alongside, same era.
Exploring automatic music annotation with acoustically-objective tags
Tingle, D., Kim, Y. E., and Turnbull, D · 2010
Cited alongside, same era.
Auditing algorithms: Research methods for detecting discrimination on internet platforms
Sandvig, C., Hamilton, K., Karahalios, K., and Langbort, C · 2014
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Explore-exploit in top-n recommender systems via gaussian processes
Vanchinathan, H. P., Nikolic, I., De Bona, F., and Krause, A · 2014
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A probabilistic model for using social networks in personalized item recommendation
Chaney, A. J., Blei, D. M., and Eliassi-Rad, T · 2015
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TrustSVD: Collaborative filtering with both the explicit and implicit influence of user trust and of item ratings
Guo, G., Zhang, J., and Yorke-Smith, N · 2015
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A probabilistic model to resolve diversity-accuracy challenge of recommendation systems
Javari, A., and Jalili, M · 2015
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Solving the apparent diversity-accuracy dilemma of recommender systems
Zhou, T., Kuscsik, Z., Liu, J.-G., Medo, M., Wakeling, J. R., and Zhang, Y.-C · 2010
Cited alongside, same era.
Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms
Li, L., Chu, W., Langford, J., and Wang, X · 2011
Cited alongside, same era.
Recommender systems with social regularization
Ma, H., Zhou, D., Liu, C., Lyu, M. R., and King, I · 2011
Cited alongside, same era.
Recommender Systems Handbook
Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B · 2011
Cited alongside, same era.
Collaborative topic modeling for recommending scientific articles
Wang, C., and Blei, D. M · 2011
Cited alongside, same era.
Probabilistic topic models
Blei, D. M · 2012
Cited alongside, same era.
Estimating the causal impact of recommendation systems from observational data
Sharma, A., Hofman, J. M., and Watts, D. J · 2015
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Modeling mutual feedback between users and recommender systems
Zeng, A., Yeung, C. H., Medo, M., and Zhang, Y.-C · 2015
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Data and algorithmic bias in the web
Baeza-Yates, R · 2016
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The racist algorithm
Chander, A · 2016
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European union regulations on algorithmic decision-making and a" right to explanation"
Goodman, B., and Flaxman, S · 2016
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The movielens datasets: History and context
Harper, F. M., and Konstan, J. A · 2016
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Modeling user exposure in recommendation
Liang, D., Charlin, L., McInerney, J., and Blei, D. M · 2016
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Recommendations as treatments: Debiasing learning and evaluation
Schnabel, T., Swaminathan, A., Singh, A., Chandak, N., and Joachims, T · 2016
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The effect of recommendations on network structure
Su, J., Sharma, A., and Goel, S · 2016
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Diversity in big data: A review
Drosou, M., Jagadish, H., Pitoura, E., and Stoyanovich, J · 2017
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How to escape your political bubble for a clearer view
Hess, A · 2017
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Diversity, serendipity, novelty, and coverage: A survey and empirical analysis of beyond-accuracy objectives in recommender systems
Kaminskas, M., and Bridge, D · 2017
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Introducing thumbs
Netflix · 2017
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Human interaction with recommendation systems: On bias and exploration
Schmit, S., and Riquelme, C · 2017
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Up next: A better recommendation system
Diresta, R · 2018
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Youtube, the great radicalizer
Tufekci, Z · 2018
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