Manel Slokom

27 papers A 2C 4Journal 11Unranked 8
YearRankTypeTitle / 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