An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Shilling recommender systems for fun and profit
Proceedings of the 13th international conference on World Wide Web
Web usage mining based on probabilistic latent semantic analysis
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness
ACM Transactions on Internet Technology (TOIT)
Model-based collaborative filtering as a defense against profile injection attacks
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Attack resistant collaborative filtering
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
The information cost of manipulation-resistance in recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
PITTCULT: trust-based cultural event recommender
Proceedings of the 2008 ACM conference on Recommender systems
Collaborative web search: a robustness analysis
Artificial Intelligence Review
Manipulation-resistant recommender systems through influence limits
ACM SIGecom Exchanges
Unsupervised strategies for shilling detection and robust collaborative filtering
User Modeling and User-Adapted Interaction
Collaborative filtering for orkut communities: discovery of user latent behavior
Proceedings of the 18th international conference on World wide web
Manipulation-resistant collaborative filtering systems
Proceedings of the third ACM conference on Recommender systems
Recsplorer: recommendation algorithms based on precedence mining
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Interactive recommendations in social endorsement networks
Proceedings of the fourth ACM conference on Recommender systems
Dependable filtering: Philosophy and realizations
ACM Transactions on Information Systems (TOIS)
Word AdHoc Network: Using Google Core Distance to extract the most relevant information
Knowledge-Based Systems
Association rule mining for mobile map personalisation
International Journal of Intelligent Systems Technologies and Applications
On-demand feature recommendations derived from mining public product descriptions
Proceedings of the 33rd International Conference on Software Engineering
Neighborhood-restricted mining and weighted application of association rules for recommenders
WISE'10 Proceedings of the 11th international conference on Web information systems engineering
Beyond the usual suspects: context-aware revisitation support
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
A layered approach to revisitation prediction
ICWE'11 Proceedings of the 11th international conference on Web engineering
Client- and server-side revisitation prediction with SUPRA
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
An expandable recommendation system on IPTV
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
Improving recommendation accuracy based on item-specific tag preferences
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
βP: A novel approach to filter out malicious rating profiles from recommender systems
Decision Support Systems
Defending recommender systems by influence analysis
Information Retrieval
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Standard memory-based collaborative filtering algorithms, such as k-nearest neighbor, are quite vulnerable to profile injection attacks. Previous work has shown that some model-based techniques are more robust than k-nn. Model abstraction can inhibit certain aspects of an attack, providing an algorithmic approach to minimizing attack effectiveness. In this paper, we examine the robustness of a recommendation algorithm based on the data mining technique of association rule mining. Our results show that the Apriori algorithm offers large improvement in stability and robustness compared to k-nearest neighbor and other model-based techniques we have studied. Furthermore, our results show that Apriori can achieve comparable recommendation accuracy to k-nn.