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Studying the Impact of Data Disclosure Mechanism in Recommender Systems via Simulation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s00778-021-00700-6openalex-snapshot
Fast-adapting and privacy-preserving federated recommender system
inferredcites →https://doi.org/10.1007/s11257-015-9165-3openalex-snapshot
What recommenders recommend: an analysis of recommendation biases and possible countermeasures
inferredcites →https://doi.org/10.1016/j.ijhcs.2019.03.002openalex-snapshot
Proactive vs. reactive personalization: Can customization of privacy enhance user experience?
inferredcites →https://doi.org/10.1016/s0898-1221(96)90463-0openalex-snapshot
Advances in neural information processing systems 7
inferredcites →https://doi.org/10.1016/s0925-2312(00)00324-6openalex-snapshot
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1109/icdm.2018.00035openalex-snapshot
Self-Attentive Sequential Recommendation
inferredcites →https://doi.org/10.1109/icra9996.2006openalex-snapshot
Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.
inferredcites →https://doi.org/10.1109/iros.2000.893120openalex-snapshot
Proceedings 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems [IROS 2000]
inferredcites →https://doi.org/10.1109/jsac.2017.2659078openalex-snapshot
Information Credibility Modeling in Cooperative Networks: Equilibrium and Mechanism Design
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/mic.2003.1167344openalex-snapshot
Amazon.com recommendations: item-to-item collaborative filtering
inferredcites →https://doi.org/10.1109/mits.2020.2990189openalex-snapshot
A Cooperative Multiagent System for Traffic Signal Control Using Game Theory and Reinforcement Learning
inferredcites →https://doi.org/10.1109/secpri.2002openalex-snapshot
Proceedings 2002 IEEE Symposium on Security and Privacy
inferredcites →https://doi.org/10.1109/sp.2019.00029openalex-snapshot
Exploiting Unintended Feature Leakage in Collaborative Learning
inferredcites →https://doi.org/10.1109/tits.2019.2901791openalex-snapshot
Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control
inferredcites →https://doi.org/10.1109/tkde.2018.2805356openalex-snapshot
Privacy Enhanced Matrix Factorization for Recommendation with Local Differential Privacy
inferredcites →https://doi.org/10.1109/tsg.2012.2203341openalex-snapshot
Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design
inferredcites →https://doi.org/10.1111/j.1540-4560.1977.tb01880.xopenalex-snapshot
Privacy as a Concept and a Social Issue: A Multidimensional Developmental Theory
inferredcites →https://doi.org/10.1145/1408664openalex-snapshot
Proceedings of the 4th symposium on Usable privacy and security
inferredcites →https://doi.org/10.1145/1557019.1557090openalex-snapshot
Differentially private recommender systems
inferredcites →https://doi.org/10.1145/1772690.1772773openalex-snapshot
Factorizing personalized Markov chains for next-basket recommendation
inferredcites →https://doi.org/10.1145/2365952.2365966openalex-snapshot
Inspectability and control in social recommenders
inferredcites →https://doi.org/10.1145/2507157.2507190openalex-snapshot
Differential data analysis for recommender systems
inferredcites →https://doi.org/10.1145/2783258.2783273openalex-snapshot
Collaborative Deep Learning for Recommender Systems
inferredcites →https://doi.org/10.1145/2792838.2800173openalex-snapshot
Applying Differential Privacy to Matrix Factorization
inferredcites →https://doi.org/10.1145/2959100.2959190openalex-snapshot
Deep Neural Networks for YouTube Recommendations
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3219819.3219890openalex-snapshot
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
inferredcites →https://doi.org/10.1145/3240323.3240370openalex-snapshot
How algorithmic confounding in recommendation systems increases homogeneity and decreases utility
inferredcites →https://doi.org/10.1145/3240323.3240399openalex-snapshot
Exploring recommendations under user-controlled data filtering
inferredcites →https://doi.org/10.1145/3269206.3271761openalex-snapshot
Recurrent Neural Networks with Top-k Gains for Session-based Recommendations
inferredcites →https://doi.org/10.1145/3357384.3357814openalex-snapshot
Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
inferredcites →https://doi.org/10.1145/3394138openalex-snapshot
Practical Privacy Preserving POI Recommendation
inferredcites →https://doi.org/10.1145/3394486.3403176openalex-snapshot
FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems
inferredcites →https://doi.org/10.1145/3394486.3403226openalex-snapshot
On Sampled Metrics for Item Recommendation
inferredcites →https://doi.org/10.1145/3397271.3401081openalex-snapshot
Meta Matrix Factorization for Federated Rating Predictions
inferredcites →https://doi.org/10.1145/3433638openalex-snapshot
The limits of differential privacy (and its misuse in data release and machine learning)
inferredcites →https://doi.org/10.1145/3437963openalex-snapshot
Proceedings of the 14th ACM International Conference on Web Search and Data Mining
inferredcites →https://doi.org/10.1145/3442381.3449965openalex-snapshot
Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy
inferredcites →https://doi.org/10.1145/3460231.3474262openalex-snapshot
Stronger Privacy for Federated Collaborative Filtering With Implicit Feedback
inferredcites →https://doi.org/10.1145/3535101openalex-snapshot
Graph Neural Networks in Recommender Systems: A Survey
inferredcites →https://doi.org/10.1145/3548606openalex-snapshot
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
inferredcites →https://doi.org/10.1145/371920.372071openalex-snapshot
Item-based collaborative filtering recommendation algorithms
inferredcites →https://doi.org/10.1145/582415.582418openalex-snapshot
Cumulated gain-based evaluation of IR techniques
inferredcites →https://doi.org/10.1287/moor.12.2.262openalex-snapshot
The Multi-Armed Bandit Problem: Decomposition and Computation
inferredcites →https://doi.org/10.1287/orsc.10.1.104openalex-snapshot
Information Privacy Concerns, Procedural Fairness, and Impersonal Trust: An Empirical Investigation
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.1561/1700000053openalex-snapshot
Privacy and Consumer Empowerment in Online Advertising
inferredcites →https://doi.org/10.1609/aaai.v33i01.33014902openalex-snapshot
Virtual-Taobao: Virtualizing Real-World Online Retail Environment for Reinforcement Learning
inferredcites →https://doi.org/10.18653/v1/2021.findings-emnlpopenalex-snapshot
Findings of the Association for Computational Linguistics: EMNLP 2021
inferredcites →https://doi.org/10.2307/249477openalex-snapshot
Information Privacy: Measuring Individuals’ Concerns About Organizational Practices1
inferredcites →https://doi.org/10.48550/arxiv.1705.08804openalex-snapshot
Beyond Parity: Fairness Objectives for Collaborative Filtering
inferredcites →https://doi.org/10.48550/arxiv.1707.07435openalex-snapshot
Deep Learning based Recommender System: A Survey and New Perspectives
inferredcites →https://doi.org/10.48550/arxiv.1905.12767openalex-snapshot
Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology
inferredcites →https://doi.org/10.48550/arxiv.2002.02126openalex-snapshot
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2011.07931openalex-snapshot
Do Offline Metrics Predict Online Performance in Recommender Systems?
inferredcites →https://doi.org/10.48550/arxiv.2101.04526openalex-snapshot
Measuring Recommender System Effects with Simulated Users
inferredcites →https://doi.org/10.48550/arxiv.2107.08959openalex-snapshot
T-RECS: A Simulation Tool to Study the Societal Impact of Recommender Systems
inferredcites →https://doi.org/10.52202/085713openalex-snapshot
Advances in Neural Information Processing Systems 19
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-23925-9_33openalex-snapshot
Progressive Disclosure of User Preferences in a Tourism Recommender System
inferred← citeshttps://doi.org/10.1080/10447318.2023.2278933openalex-snapshot
Recommendations with Benefits: Exploring Explanations in Information Sharing Recommender Systems for Temporary Teams
inferred← citeshttps://doi.org/10.1109/icact67549.2025.11351371openalex-snapshot
E-Commerce Data Analysis and Visualization Using Python: A Case Study of Amazon and Flipkart
inferred← citeshttps://doi.org/10.1109/tkde.2025.3579807openalex-snapshot
GCPA: GAN-Based Collusive Poisoning Attack in Federated Recommender Systems
inferred← citeshttps://doi.org/10.1145/3579995openalex-snapshot
Trustworthy Recommendation and Search: Introduction to the Special Issue - Part 1
inferred← citeshttps://doi.org/10.1145/3658644.3670365openalex-snapshot
Not One Less: Exploring Interplay between User Profiles and Items in Untargeted Attacks against Federated Recommendation
inferred← citeshttps://doi.org/10.1145/3715275.3732195openalex-snapshot
The Data Minimization Principle in Machine Learning
inferred← citeshttps://doi.org/10.1145/3767695.3769497openalex-snapshot
Data Usage Privacy Auditing for Semi-supervised GNNs
inferred← citeshttps://doi.org/10.1145/3771093openalex-snapshot
D-RecSys: A Decentralized Recommendation Framework for Web 3.0-Based Content-Sharing Platforms
inferred← citeshttps://doi.org/10.1257/rct.10667-2.0openalex-snapshot
Decentralized Feature Selection - The Impacts of User-Control over Feature Selection on the Acceptance and Performance of Recommender Systems
inferred← citeshttps://doi.org/10.3390/app13106201openalex-snapshot
A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems
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