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When and how to diversify : a multicategory utility model for personalized content recommendation

Song, Yicheng; Sahoo, Nachiketa; Ofek, Elie - In: Management science : journal of the Institute for … 65 (2019) 8, pp. 3737-3757

Persistent link: https://www.econbiz.de/10012062768

A fuzzy hybrid approach to enhance diversity in top-N recommendations

Maatallah, Majda; Seridi-Bouchelaghem, Hassina - In: International journal of business information systems : … 19 (2015) 4, pp. 505-530

Persistent link: https://www.econbiz.de/10011405922

Prick the filter bubble : a novel cross domain recommendation model with adaptive diversity regularization

Sun, Jianshan; Song, Jian; Jiang, Yuanchun; Liu, Yezheng; … - In: Electronic markets : EM ; the international journal of … 32 (2022) 1, pp. 101-121

Persistent link: https://www.econbiz.de/10013271598

The impact of consumer preferences on the accuracy of collaborative filtering recommender systems

Köhler, Sebastian; Wöhner, Thomas; Peters, Ralf - In: Electronic markets : the international journal on … 26 (2016) 4, pp. 369-379

Persistent link: https://www.econbiz.de/10011666996

Learning preferences with side information

Farias, Vivek F.; Li, Andrew A. - In: Management science : journal of the Institute for … 65 (2019) 7, pp. 3131-3149

Persistent link: https://www.econbiz.de/10012039981

How do recommender systems affect sales diversity? : a cross-category investigation via randomized field experiment

Lee, Dokyun; Hosanagar, Kartik - In: Information systems research : ISR 30 (2019) 1, pp. 239-259

Persistent link: https://www.econbiz.de/10012038222

Integrating individual and aggregate diversity in top-n recommendation

Çanakoğlu, Ethem; Muter, İbrahim; Aytekin, Tevfik - In: INFORMS journal on computing : JOC 33 (2021) 1, pp. 300-318

Persistent link: https://www.econbiz.de/10012496403

Consumer acquisition for recommender systems : a theoretical framework and empirical evaluations

Bi, Xuan; Yang, Mochen; Adomavicius, Gediminas - In: Information systems research : ISR 35 (2024) 1, pp. 339-362

Persistent link: https://www.econbiz.de/10014530464

Collaborative filtering recommender systems : methods, strengths and weaknesses

Schmidtke, Marcel; Neeb, Jannik; Wöhner, Thomas - 2025

Recommender systems are indispensable in e-business due to the extensive product range and the large number of niche articles. Collaborative filtering (CF) algorithms play a central role in generating personalised recommendations. There are numerous CF approaches in the literature that have...

Persistent link: https://www.econbiz.de/10015374761

A model to improve recommendation systems based on Spark platform

Abdel-Fattah, Manal A. - In: International journal of business information systems : … 39 (2022) 3, pp. 328-348

Persistent link: https://www.econbiz.de/10013198417