Simulating real profiles for shilling attacks: A generative approach-Reference-Cited by-同舟云学术

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Simulating real profiles for shilling attacks: A generative approach

Published:2021-10 Issue: Volume:230 Page:107390
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Barbieri Julio^ORCID,Alvim Leandro G.M.^ORCID,Braida Filipe^ORCID,Zimbrão Geraldo^ORCID

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference51 articles.

1. The impact of youtube recommendation system on video views;Zhou,2010

2. Recommender systems in e-commerce;Schafer,1999

3. Employing rough set theory to alleviate the sparsity issue in recommender system;Huang,2008

4. Multi-linear interactive matrix factorization;Yu;Know.-Based Syst.,2015

5. Tiirec: A tensor approach for tag-driven item recommendation with sparse user generated content;Yu,2017

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures;ACM Computing Surveys;2024-07-25

2. A Research on Shilling Attacks Based on Variational graph auto-encoders for Improving the Robustness of Recommendation Systems;Proceedings of the 2024 International Conference on Generative Artificial Intelligence and Information Security;2024-05-10

3. Improving Deep Learning-Based Recommendation Attack Detection Using Harris Hawks Optimization;Applied Sciences;2022-10-09

4. Detecting shilling groups in online recommender systems based on graph convolutional network;Information Processing & Management;2022-09

5. Collaborative filtering recommendation using fusing criteria against shilling attacks;Connection Science;2022-06-14

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