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With the uptake of algorithmic personalization in the news domain, news organizations increasingly trust automated systems with previously considered editorial responsibilities, e.g., prioritizing news to readers.
Implicit Feedback for Recommender Systems. In in Proceedings of the AAAI Workshop on Recommender Systems . 81–83
Douglas Oard and Jinmook Kim. 1998 · 1998
Earlier work this paper cites.
Improving recommendation diversity. In Proceedings of the Twelfth Irish Conference on Artificial Intelligence and Cognitive Science, Maynooth, Ireland . 85–94
Keith Bradley and Barry Smyth. 2001 · 2001
Earlier work this paper cites.
Being accurate is not enough: how accuracy metrics have hurt recommender systems. In CHI’06 extended abstracts on Human factors in computing systems . 1097–1101
Sean M McNee, John Riedl, and Joseph A Konstan. 2006 · 2006
Earlier work this paper cites.
Search Engines that Learn from Implicit Feedback
T. Joachims and F. Radlinski. 2007 · 2007
Earlier work this paper cites.
Beyond Accuracy: Evaluating Recommender Systems by Coverage and Serendipity. In Proceedings of the Fourth ACM Conference on Recommender Systems (Barcelona, Spain) (RecSys ’10) . Association for Computing Machinery, New York, NY, USA, 257–260
Mouzhi Ge, Carla Delgado-Battenfeld, and Dietmar Jannach. 2010 · 2010
Earlier work this paper cites.
Temporal diversity in recommender systems. In Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval . ACM, 210–217
Neal Lathia, Stephen Hailes, Licia Capra, and Xavier Amatriain. 2010 · 2010
Earlier work this paper cites.
Introduction to recommender systems handbook
Francesco Ricci, Lior Rokach, and Bracha Shapira. 2011 · 2011
Earlier work this paper cites.
Evaluating recommendation systems
Guy Shani and Asela Gunawardana. 2011 · 2011
Earlier work this paper cites.
Rank and Relevance in Novelty and Diversity Metrics for Recommender Systems. In Proceedings of the Fifth ACM Conference on Recommender Systems (Chicago, Illinois, USA) (RecSys ’11) . Association for Computing Machinery, New York, NY, USA, 109–116
Saúl Vargas and Pablo Castells. 2011 · 2011
Earlier work this paper cites.
The plista dataset. In Proceedings of the 2013 International News Recommender Systems Workshop and Challenge . 16–23
Benjamin Kille, Frank Hopfgartner, Torben Brodt, and Tobias Heintz. 2013 · 2013
Earlier work this paper cites.
Offline and Online Evaluation of News Recommender Systems at Swissinfo.Ch. In Proceedings of the 8th ACM Conference on Recommender Systems (Foster City, Silicon Valley, California, USA) (RecSys ’14) . Association for Computing Machinery, New York, NY, USA, 169–176
Florent Garcin, Boi Faltings, Olivier Donatsch, Ayar Alazzawi, Christophe Bruttin, and Amr Huber. 2014 · 2014
Cited alongside, same era.
Practical Lessons from Predicting Clicks on Ads at Facebook
Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Ralf Herbrich, Stuart Bowers, et al · 2014
Cited alongside, same era.
Xgboost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining . 785–794
Tianqi Chen and Carlos Guestrin. 2016 · 2016
Cited alongside, same era.
Diversity, Serendipity, Novelty, and Coverage: A Survey and Empirical Analysis of Beyond-Accuracy Objectives in Recommender Systems
Marius Kaminskas and Derek Bridge. 2016 · 2016
Cited alongside, same era.
SMART Radio: Personalized News Radio
Maya Sappelli, Dung Manh Chu, Bahadir Cambel, Joeri Nortier, and David Graus. 2018b · 2018
Later among the works it cites.
My Friends, Editors, Algorithms, and I
Neil Thurman, Judith Möller, Natali Helberger, and Damian Trilling. 2019 · 2018
Later among the works it cites.
Are You Reaching Your Audience? Exploring Item Exposure over Consumer Segments in Recommender Systems. In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (Singapore, Singapore) (UMAP ’18) . Association for Computing Machinery, New York, NY, USA, 213–217
Jacek Wasilewski and Neil Hurley. 2018 · 2018
Later among the works it cites.
Safeguarding the journalistic DNA. Attitudes towards value-sensitive algorithm design in news. In Conference paper presented at “The future of journalism conference” (Cardiff, Wales)
Mariella Bastian and Natali Helberger. 2019 · 2019
Later among the works it cites.
Selling News to Audiences – A Qualitative Inquiry into the Emerging Logics of Algorithmic News Personalization in European Quality News Media
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An Analysis on Time- and Session-Aware Diversification in Recommender Systems. In Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization (Bratislava, Slovakia) (UMAP ’17) . Association for Computing Machinery, New York, NY, USA, 270–274
Vito W. Anelli, Vito Bellini, Tommaso Di Noia, Wanda La Bruna, Paolo Tomeo, and Eugenio Di Sciascio. 2017 · 2017
Cited alongside, same era.
Practical lessons from developing a large-scale recommender system at Zalando. In Proceedings of the Eleventh ACM Conference on Recommender Systems . 251–259
Antonino Freno. 2017 · 2017
Cited alongside, same era.
Online Learning to Rank for Recommender Systems. In Proceedings of the Eleventh ACM Conference on Recommender Systems (Como, Italy) (RecSys ’17) . Association for Computing Machinery, New York, NY, USA, 348
Daan Odijk and Anne Schuth. 2017 · 2017
Cited alongside, same era.
Interested in Diversity
Balázs Bodó, Natali Helberger, Sarah Eskens, and Judith Möller. 2019 · 2018
Cited alongside, same era.
Automating judgment? Algorithmic judgment, news knowledge, and journalistic professionalism
Matt Carlson. 2018 · 2018
Cited alongside, same era.
News recommender systems – Survey and roads ahead
Mozhgan Karimi, Dietmar Jannach, and Michael Jugovac. 2018 · 2018
Cited alongside, same era.
SMART Journalism: Personalizing, Summarizing, and Recommending Financial Economic News. In The Algorithmic Personalization and News (APEN18) Workshop at ICWSM , Vol. 18
Maya Sappelli, Dung Manh Chu, Bahadir Cambel, David Graus, and Philippe Bressers. 2018a
Cited in the paper.
Balázs Bodó. 2019 · 2019
Later among the works it cites.
On the Democratic Role of News Recommenders
Natali Helberger. 2019 · 2019
Later among the works it cites.
Measuring the Business Value of Recommender Systems
Dietmar Jannach and Michael Jugovac. 2019 · 2019
Later among the works it cites.
Reading News with a Purpose: Explaining User Profiles for Self-Actualization. In Proceedings of 27th Conference on User Modeling, Adaptation and Personalization Adjunct . ACM
Emily Sullivan, Dimitrios Bountouridis, Jaron Harambam, Shabnam Najafian, Felicia Löcherbach, Mykola Makhortykh, Domokos Kelen, Daricia Wilkinson, David Graus, and Nava Tintarev. 2019 · 2019
Later among the works it cites.
Know your algorithm: what media organizations need to explain to their users about news personalization
M Z van Drunen, N Helberger, and M Bastian. 2019 · 2019
Later among the works it cites.
UMAP2020 - Beyond Optimizing for Clicks - Supplementary Material
Feng Lu, Anca Dumitrache, and David Graus. 2020 · 2020
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