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
来源：
ACM SIGECOM EXCHANGES | 2008年 / 7卷 / 03期
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
  • [21] Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems
    Bojic, Ljubisa
    Zaric, Maja
    Zikic, Simona
    ETNOANTROPOLOSKI PROBLEMI-ISSUES IN ETHNOLOGY AND ANTHROPOLOGY, 2021, 16 (03): : 935 - 957
  • [22] A Particle Swarm Approach to Collaborative Filtering based Recommender Systems through Fuzzy Features
    Wasid, Mohammed
    Kant, Vibhor
    ELEVENTH INTERNATIONAL CONFERENCE ON COMMUNICATION NETWORKS, ICCN 2015/INDIA ELEVENTH INTERNATIONAL CONFERENCE ON DATA MINING AND WAREHOUSING, ICDMW 2015/NDIA ELEVENTH INTERNATIONAL CONFERENCE ON IMAGE AND SIGNAL PROCESSING, ICISP 2015, 2015, 54 : 440 - 448
  • [23] Affective recommender systems in online news industry: how emotions influence reading choices
    Jan Mizgajski
    Mikołaj Morzy
    User Modeling and User-Adapted Interaction, 2019, 29 : 345 - 379
  • [24] A Case Study on Recommender Systems in Online Conferences: Behavioral Analysis through A/B Testing
    Okoso, Ayano
    Otaki, Keisuke
    Ishii, Yoshinao
    Koide, Satoshi
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2024, E107D (05) : 650 - 658
  • [25] Affective recommender systems in online news industry: how emotions influence reading choices
    Mizgajski, Jan
    Morzy, Mikolaj
    USER MODELING AND USER-ADAPTED INTERACTION, 2019, 29 (02) : 345 - 379
  • [26] Personalized finance advisory through case-based recommender systems and diversification strategies
    Musto, Cataldo
    Semeraro, Giovanni
    Lops, Pasquale
    de Gemmis, Marco
    Lekkas, Georgios
    DECISION SUPPORT SYSTEMS, 2015, 77 : 100 - 111
  • [27] A Novel Architecture for Enhancing Museum Visits Through Recommender Systems, Digital Storytelling, and NFT
    Casillo, Mario
    Gaeta, Rosario
    Lorusso, Angelo
    Marongiu, Francesco
    Santaniello, Domenico
    Valentino, Carmine
    PROCEEDINGS OF NINTH INTERNATIONAL CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGY, VOL 9, ICICT 2024, 2025, 1054 : 121 - 130
  • [28] Social influence for societal interest: a pro-ethical framework for improving human decision making through multi-stakeholder recommender systems
    Fabbri, Matteo
    AI & SOCIETY, 2023, 38 (02) : 995 - 1002
  • [29] Social influence for societal interest: a pro-ethical framework for improving human decision making through multi-stakeholder recommender systems
    Matteo Fabbri
    AI & SOCIETY, 2023, 38 : 995 - 1002
  • [30] User's Dilemma: A Qualitative Study on the Influence of Netflix Recommender Systems on Choice Overload
    Meza, Laura Romero
    D'Urso, Giulio
    PSYCHOLOGICAL STUDIES, 2024, 69 (03) : 349 - 367
12345