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Overlapping Community Regularization for Rating Prediction in Social Recommender Systems

Published: 16 September 2015 Publication History

Abstract

Recommender systems have become de facto tools for suggesting items that are of potential interest to users. Predicting a user's rating on an item is the fundamental recommendation task. Traditional methods that generate predictions by analyzing the user-item rating matrix perform poorly when the matrix is sparse. Recent approaches use data from social networks to improve accuracy. However, most of the social-network based recommender systems only consider direct friendships and they are less effective when the targeted user has few social connections. In this paper, we propose two alternative models that incorporate the overlapping community regularization into the matrix factorization framework. Our empirical study on four real datasets shows that our approaches outperform the state-of-the-art algorithms in both traditional and social-network based recommender systems regarding both cold-start users and normal users.

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  • (2025)Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient EstimationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.348424937:1(162-173)Online publication date: Jan-2025
  • (2025)Causal disentanglement for regulating social influence bias in social recommendationNeurocomputing10.1016/j.neucom.2024.129133618(129133)Online publication date: Feb-2025
  • (2023)Recommendation System: A Survey and New PerspectivesWorld Scientific Annual Review of Artificial Intelligence10.1142/S281103232330001301Online publication date: 4-May-2023
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        cover image ACM Conferences
        RecSys '15: Proceedings of the 9th ACM Conference on Recommender Systems
        September 2015
        414 pages
        ISBN:9781450336925
        DOI:10.1145/2792838
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Publication History

        Published: 16 September 2015

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        Author Tags

        1. matrix factorization
        2. overlapping community regularization
        3. rating prediction
        4. social recommender systems

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        RecSys '15
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        RecSys '15: Ninth ACM Conference on Recommender Systems
        September 16 - 20, 2015
        Vienna, Austria

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        RecSys '15 Paper Acceptance Rate 28 of 131 submissions, 21%;
        Overall Acceptance Rate 254 of 1,295 submissions, 20%

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        Cited By

        View all
        • (2025)Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient EstimationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.348424937:1(162-173)Online publication date: Jan-2025
        • (2025)Causal disentanglement for regulating social influence bias in social recommendationNeurocomputing10.1016/j.neucom.2024.129133618(129133)Online publication date: Feb-2025
        • (2023)Recommendation System: A Survey and New PerspectivesWorld Scientific Annual Review of Artificial Intelligence10.1142/S281103232330001301Online publication date: 4-May-2023
        • (2023)Semantic and Structural View Fusion Modeling for Social RecommendationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.323097235:11(11872-11884)Online publication date: 1-Nov-2023
        • (2023)TAG: Joint Triple-Hierarchical Attention and GCN for Review-Based Social Recommender SystemIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.319495235:10(9904-9919)Online publication date: 1-Oct-2023
        • (2022)Disentangled Contrastive Learning for Social RecommendationProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557583(4570-4574)Online publication date: 17-Oct-2022
        • (2022)DiffNet++: A Neural Influence and Interest Diffusion Network for Social RecommendationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.304841434:10(4753-4766)Online publication date: 1-Oct-2022
        • (2022)Multi-Task Learning for Recommendation Over Heterogeneous Information NetworkIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.298340934:2(789-802)Online publication date: 1-Feb-2022
        • (2022)A human-centered decentralized architecture and recommendation engine in SIoTUser Modeling and User-Adapted Interaction10.1007/s11257-022-09320-332:3(297-353)Online publication date: 9-Apr-2022
        • (2022)A Comparative Approach for Opinion Spam Detection Using Sentiment AnalysisProceedings of First International Conference on Computational Electronics for Wireless Communications10.1007/978-981-16-6246-1_43(511-522)Online publication date: 3-Jan-2022
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