Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Horting hatches an egg: a new graph-theoretic approach to collaborative filtering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Torture Tests: A Quantitative Analysis for the Robustness of Knowledge-Based Systems
EKAW '00 Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling and Management
Discovering robust knowledge from dynamic closed-world data
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Robustness Analyses of Instance-Based Collaborative Recommendation
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Shilling recommender systems for fun and profit
Proceedings of the 13th international conference on World Wide Web
Proceedings of the 10th international conference on Intelligent user interfaces
Adaptive recommendation: putting the best foot forward
ISICT '04 Proceedings of the 2004 international symposium on Information and communication technologies
Preventing shilling attacks in online recommender systems
Proceedings of the 7th annual ACM international workshop on Web information and data management
Is trust robust?: an analysis of trust-based recommendation
Proceedings of the 11th international conference on Intelligent user interfaces
The influence limiter: provably manipulation-resistant recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
A hybrid framework for similarity-based recommendations
International Journal of Business Intelligence and Data Mining
The information cost of manipulation-resistance in recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Manipulation-resistant recommender systems through influence limits
ACM SIGecom Exchanges
Trustworthy knowledge diffusion model based on risk discovery on peer-to-peer networks
Expert Systems with Applications: An International Journal
Multidimensional credibility model for neighbor selection in collaborative recommendation
Expert Systems with Applications: An International Journal
Proceedings of the third ACM conference on Recommender systems
A live-user evaluation of collaborative web search
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Trust no one: evaluating trust-based filtering for recommenders
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Dependable filtering: Philosophy and realizations
ACM Transactions on Information Systems (TOIS)
Analysis of robustness in trust-based recommender systems
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
A Case Study of Collaboration and Reputation in Social Web Search
ACM Transactions on Intelligent Systems and Technology (TIST)
Robustness of recommender systems
Proceedings of the fifth ACM conference on Recommender systems
Building and managing reputation in the environment of Chinese e-commerce: a case study on Taobao
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
βP: A novel approach to filter out malicious rating profiles from recommender systems
Decision Support Systems
When power users attack: assessing impacts in collaborative recommender systems
Proceedings of the 7th ACM conference on Recommender systems
Accuracy and robustness impacts of power user attacks on collaborative recommender systems
Proceedings of the 7th ACM conference on Recommender systems
Campaign extraction from social media
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
Robustness analysis of privacy-preserving model-based recommendation schemes
Expert Systems with Applications: An International Journal
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The growth and popularity of Internet applications has reinforced the need for effective information filtering techniques. The collaborative filtering approach is now a popular choice and has been implemented in many on-line systems. While many researchers have proposed and compared the performance of various collaborative filtering algorithms, one important performance measure has been omitted from the research to date -that is the robustness of the algorithm. In essence, robustness measures the power of the algorithm to make good predictions in the presence of noisy data. In this paper, we argue that robustness is an important system characteristic, and that it must be considered from the point-of-view of potential attacks that could be made on a system by malicious users. We propose a definition for system robustness, and identify system characteristics that influence robustness. Several attack strategies are described in detail, and experimental results are presented for the scenarios outlined.