Manel Slokom - RankMe

27 papers A 2C 4Journal 11Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LLMDiRec: LLM-Enhanced Intent Diffusion for Sequential Recommendation. CoRR Bo-Chian Chen, Manel Slokom
2026	—	`conf`	SynIRgy: Synthetic Data and Simulation Synergy for Information Retrieval. ECIR (3) Manel Slokom, Alejandro Bellogín, Mayank Singh, Andrea Barraza-Urbina
2025	J	`jnl`	FedFlex: Federated Learning for Diverse Netflix Recommendations. CoRR Sven Lankester, Manel Slokom, Gustavo de Carvalho Bertoli, Matias Vizcaino, Emmanuelle Beauxis-Aussalet, Laura Hollink
2025	—	`conf`	How to Diversify any Personalized Recommender? ECIR (4) Manel Slokom, Savvina Daniil, Laura Hollink
2025	J	`jnl`	On the challenges of studying bias in Recommender Systems: The effect of data characteristics and algorithm configuration. Inf. Retr. Res. J. Savvina Daniil, Manel Slokom, Mirjam Cuper, Cynthia C. S. Liem, Jacco van Ossenbruggen, Laura Hollink
2024	C	`conf`	A Case Study Exploring Data Synthesis Strategies on Tabular vs. Aggregated Data Sources for Official Statistics. PSD Mohamed Aghaddar, Liu Nuo Su, Manel Slokom, Lucas Barnhoorn, Peter-Paul de Wolf
2024	J	`jnl`	How to Diversify any Personalized Recommender? A User-centric Pre-processing approach. CoRR Manel Slokom, Laura Hollink
2024	J	`jnl`	On the challenges of studying bias in Recommender Systems: A UserKNN case study. CoRR Savvina Daniil, Manel Slokom, Mirjam Cuper, Cynthia C. S. Liem, Jacco van Ossenbruggen, Laura Hollink
2024	C	`conf`	Relational Or Single: A Comparative Analysis of Data Synthesis Approaches for Privacy and Utility on a Use Case from Statistical Office. PSD Manel Slokom, Shruti Agrawal, Nynke C. Krol, Peter-Paul de Wolf
2024	—	`conf`	Technological Innovation in the Media Sector: Understanding Current Practices and Unraveling Opportunities. CHI Extended Abstracts Simone Ooms, Pablo César, Abdallah El Ali, Davide Ceolin, Laura Hollink, Manel Slokom, Eric J. Pauwels, Valentin Robu, Han La Poutré
2024	—	`—`	Towards Purpose-aware Privacy-Preserving Techniques for Predictive Applications. Manel Slokom
2023	C	`conf`	Exploring Privacy-Preserving Techniques on Synthetic Data as a Defense Against Model Inversion Attacks. ISC Manel Slokom, Peter-Paul de Wolf, Martha A. Larson
2023	J	`jnl`	When Machine Learning Models Leak: An Exploration of Synthetic Training Data. CoRR Manel Slokom, Peter-Paul de Wolf, Martha A. Larson
2022	J	`jnl`	Gender In Gender Out: A Closer Look at User Attributes in Context-Aware Recommendation. CoRR Manel Slokom, Özlem Özgöbek, Martha A. Larson
2022	—	`ch.`	Machine Learning Meets Data Modification - The Potential of Pre-processing for Privacy Enchancement. Security and Artificial Intelligence Giuseppe Garofalo, Manel Slokom, Davy Preuveneers, Wouter Joosen, Martha A. Larson
2022	J	`jnl`	Minimizing Mindless Mentions: Recommendation with Minimal Necessary User Reviews. CoRR Danny Stax, Manel Slokom, Martha A. Larson
2022	C	`conf`	When Machine Learning Models Leak: An Exploration of Synthetic Training Data. PSD Manel Slokom, Peter-Paul de Wolf, Martha A. Larson
2021	J	`jnl`	Doing Data Right: How Lessons Learned Working with Conventional Data should Inform the Future of Synthetic Data for Recommender Systems. CoRR Manel Slokom, Martha A. Larson
2021	A	`conf`	SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research. RecSys Michael D. Ekstrand, Allison Chaney, Pablo Castells, Robin Burke, David Rohde, Manel Slokom
2021	J	`jnl`	Towards user-oriented privacy for recommender system data: A personalization-based approach to gender obfuscation for user profiles. Inf. Process. Manag. Manel Slokom, Alan Hanjalic, Martha A. Larson
2020	J	`jnl`	Partially Synthetic Data for Recommender Systems: Prediction Performance and Preference Hiding. CoRR Manel Slokom, Martha A. Larson, Alan Hanjalic
2019	—	`conf`	BlurM(or)e: Revisiting Gender Obfuscation in the User-Item Matrix. RMSE@RecSys Christopher Strucks, Manel Slokom, Martha A. Larson
2019	—	`conf`	Data Masking for Recommender Systems: Prediction Performance and Rating Hiding. RecSys (Late-Breaking Results) Manel Slokom, Martha A. Larson, Alan Hanjalic
2019	—	`conf`	Up Close, but not too Personal: Hypotargeting for Recommender Systems. ImpactRS@RecSys Martha A. Larson, Manel Slokom
2018	A	`conf`	Comparing recommender systems using synthetic data. RecSys Manel Slokom
2017	—	`conf`	A New Social Recommender System Based on Link Prediction Across Heterogeneous Networks. KES-IDT (2) Manel Slokom, Raouia Ayachi
2015	—	`conf`	Towards a new possibilistic collaborative filtering approach. CSCESM Manel Slokom, Raouia Ayachi