Shlomo Berkovsky
Cited by
Cited by
Group-based recipe recommendations: analysis of data aggregation strategies
S Berkovsky, J Freyne
Proceedings of the fourth ACM conference on Recommender systems, 111-118, 2010
Mediation of user models for enhanced personalization in recommender systems
S Berkovsky, T Kuflik, F Ricci
User Modeling and User-Adapted Interaction 18 (3), 245-286, 2008
Intelligent food planning: personalized recipe recommendation
J Freyne, S Berkovsky
Proceedings of the 15th international conference on Intelligent user …, 2010
Cross-domain recommender systems
I Cantador, I Fernández-Tobías, S Berkovsky, P Cremonesi
Recommender systems handbook, 919-959, 2015
The personalization of conversational agents in health care: systematic review
AB Kocaballi, S Berkovsky, JC Quiroz, L Laranjo, HL Tong, ...
Journal of medical Internet research 21 (11), e15360, 2019
Cross-Domain Mediation in Collaborative Filtering
S Berkovsky, T Kuflik, FR Ricci
Proceedings of the 11th international conference on User Modeling (UM’07 …, 2007
Enhancing privacy and preserving accuracy of a distributed collaborative filtering
S Berkovsky, Y Eytani, T Kuflik, F Ricci
Proceedings of the 2007 ACM conference on Recommender systems, 9-16, 2007
Relating Personality Types with User Preferences in Multiple Entertainment Domains.
I Cantador, I Fernández-Tobías, A Bellogín, M Kosinski, D Stillwell
UMAP Workshops 997, 2013
Influencing individually: fusing personalization and persuasion
S Berkovsky, J Freyne, H Oinas-Kukkonen
ACM Transactions on Interactive Intelligent Systems (TiiS) 2 (2), 1-8, 2012
Physical activity motivating games: virtual rewards for real activity
S Berkovsky, M Coombe, J Freyne, D Bhandari, N Baghaei
Proceedings of the SIGCHI conference on human factors in computing systems …, 2010
Applying differential privacy to matrix factorization
A Berlioz, A Friedman, MA Kaafar, R Boreli, S Berkovsky
Proceedings of the 9th ACM Conference on Recommender Systems, 107-114, 2015
Privacy aspects of recommender systems
A Friedman, BP Knijnenburg, K Vanhecke, L Martens, S Berkovsky
Recommender systems handbook, 649-688, 2015
Detecting personality traits using eye-tracking data
S Berkovsky, R Taib, I Koprinska, E Wang, Y Zeng, J Li, S Kleitman
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems …, 2019
Features predicting weight loss in overweight or obese participants in a web-based intervention: randomized trial
E Brindal, J Freyne, I Saunders, S Berkovsky, G Smith, M Noakes
Journal of medical Internet research 14 (6), e2156, 2012
Mobile health and privacy: cross sectional study
G Tangari, M Ikram, K Ijaz, MA Kaafar, S Berkovsky
bmj 373, 2021
User trust dynamics: An investigation driven by differences in system performance
K Yu, S Berkovsky, R Taib, D Conway, J Zhou, F Chen
Proceedings of the 22nd international conference on intelligent user …, 2017
Optimal Greedy Diversity for Recommendation.
A Ashkan, B Kveton, S Berkovsky, Z Wen
IJCAI 15, 1742-1748, 2015
A differential privacy framework for matrix factorization recommender systems
A Friedman, S Berkovsky, MA Kaafar
User Modeling and User-Adapted Interaction 26, 425-458, 2016
Isocitrate dehydrogenase (IDH) status prediction in histopathology images of gliomas using deep learning
S Liu, Z Shah, A Sav, C Russo, S Berkovsky, Y Qian, E Coiera, A Di Ieva
Scientific reports 10 (1), 7733, 2020
How to recommend? User trust factors in movie recommender systems
S Berkovsky, R Taib, D Conway
Proceedings of the 22nd international conference on intelligent user …, 2017
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