Manipulation-Resistant Recommender Systems through Influence Limits

被引:0
作者
Resnick, Paul [1 ]
Sami, Rahul [1 ]
机构
[1] Univ Michigan, Sch Informat, Ann Arbor, MI 48109 USA
关键词
Algorithms; Reliability; Recommender systems; manipulation-resistance; shilling; informationloss;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
引用
收藏
页数:4
相关论文
共 45 条
  • [31] How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages?
    Lee, Dokyun
    Hosanagar, Kartik
    MANAGEMENT SCIENCE, 2021, 67 (01) : 524 - 546
  • [32] Supporting Knowledge Workers through Personal Information Assistance with Context-aware Recommender Systems
    Bakhshizadeh, Mahta
    PROCEEDINGS OF THE EIGHTEENTH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2024, 2024, : 1296 - 1301
  • [33] Enhancing Recommender Systems by Fusing Diverse Information Sources through Data Transformation and Feature Selection
    Ho, Thi-Linh
    Le, Anh-Cuong
    Vu, Dinh-Hong
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2023, 17 (05): : 1413 - 1432
  • [34] Enhancing Recommender Systems through Imputation and Social-Aware Graph Convolutional Neural Network
    Faroughi, Azadeh
    Moradi, Parham
    Jalili, Mahdi
    NEURAL NETWORKS, 2025, 184
  • [35] Modeling Tourists' Personality in Recommender Systems How Does Personality Influence Preferences for Tourist Attractions?
    Alves, Patricia
    Saraiva, Pedro
    Carneiro, Joao
    Campos, Pedro
    Martins, Helena
    Novais, Paulo
    Marreiros, Goreti
    UMAP'20: PROCEEDINGS OF THE 28TH ACM CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION, 2020, : 4 - 13
  • [36] Watch This! The Influence of Recommender Systems and Social Factors on the Content Choices of Streaming Video on Demand Consumers
    Weidhaas, Raphael
    Schloegl, Stephan
    Halttunen, Veikko
    Spiess, Teresa
    INNOVATION THROUGH INFORMATION SYSTEMS, VOL II: A COLLECTION OF LATEST RESEARCH ON TECHNOLOGY ISSUES, 2021, 47 : 738 - 753
  • [37] The Influence of Social Presence on Customer Intention to Reuse Online Recommender Systems: The Roles of Personalization and Product Type
    Choi, Jaewon
    Lee, Hong Joo
    Kim, Yong Cheol
    INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE, 2011, 16 (01) : 129 - 153
  • [38] Bots influence opinion dynamics without direct human-bot interaction: the mediating role of recommender systems
    N. Pescetelli
    D. Barkoczi
    M. Cebrian
    Applied Network Science, 7
  • [39] A Novel Evaluation Perspective on GNNs-based Recommender Systems through the Topology of the User-Item Graph
    Malitesta, Daniele
    Pomo, Claudio
    Anelli, Vito Walter
    Mancino, Alberto Carlo Maria
    Di Noia, Tommaso
    Di Sciascio, Eugenio
    PROCEEDINGS OF THE EIGHTEENTH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2024, 2024, : 549 - 559
  • [40] Bots influence opinion dynamics without direct human-bot interaction: the mediating role of recommender systems
    Pescetelli, N.
    Barkoczi, D.
    Cebrian, M.
    APPLIED NETWORK SCIENCE, 2022, 7 (01)