Robust collaborative filtering, or attack-resistant collaborative filtering, refers to algorithms or techniques that aim to make collaborative filtering more robust against efforts of manipulation, while hopefully maintaining recommendation quality. In general, these efforts of manipulation usually refer to shilling attacks, also called profile injection attacks. Collaborative filtering predicts a user's rating to items by finding similar users and looking at their ratings, and because it is possible to create nearly indefinite copies of user profiles in an online system, collaborative filtering becomes vulnerable when multiple copies of fake profiles are introduced to the system. There are several different approaches suggested to improve robustness of both model-based and memory-based collaborative filtering. However, robust collaborative filtering techniques are still an active research field, and major applications of them are yet to come.
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suggested to improve robustness of both model-based and memory-based collaborativefiltering. However, robustcollaborativefiltering techniques are still...
one. In the newer, narrower sense, collaborativefiltering is a method of making automatic predictions (filtering) about the interests of a user by collecting...
collaborators, and financial services. Recommender systems usually make use of either or both collaborativefiltering and content-based filtering (also...
disposable face masks sometimes referred to as a filtering facepiece respirator to a more robust reusable model with replaceable cartridges called an...
The Netflix Prize was an open competition for the best collaborativefiltering algorithm to predict user ratings for films, based on previous ratings...
merging, improved motion compensation filtering, and an additional filtering step called sample-adaptive offset filtering. Effective use of these improvements...
between reputation systems and collaborativefiltering is the ways in which they use user feedback. In collaborativefiltering, the goal is to find similarities...
Initiative does not check for filtering of child pornography and because their classifications focus on technical filtering, they do not include other types...
The Cognition and Neuroergonomics (CaN) Collaborative Technology Alliance was a research program initiated, sponsored and partly performed by the U.S...
assess the robustness of machine learning models and minimize the risk of adversarial attacks. Examples include attacks in spam filtering, where spam...
the DeepMind Safety team outlined AI safety problems in specification, robustness, and assurance. The following year, researchers organized a workshop at...
Roskomnadzor agency collaborates with Chinese Great Firewall security officials in implementing its data retention and filtering infrastructure. During...
computer-supported collaborative learning: A role for Social Network Analysis". International Journal of Computer-Supported Collaborative Learning. 2 (1):...
2009 Second Place in the $1 million Netflix Prize competition for collaborativefiltering 2010 Best Student Paper Award, International Conference on Machine...
software for public critical discussion, collaborative development, group commitment, and collaborativefiltering of content based on voting and rating....
servers or clients. The broker may also perform additional tasks, such as filtering, modifying messages, ensuring a quality of service (QoS) (e.g. 0 for "at...
resources and they have to be self organized. As for the distributed filtering over distributed sensor network. the general setup is to observe the underlying...
resilience of secure information infrastructure. CloudFilter (2012–13) was an EPSRC collaborative project with Imperial College to explore novel methods...
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Customers now had the ability to better configure their spam and virus filtering, implement retention policies, restore deleted messages, and give administrators...
Windows versions. One reason cited by Microsoft is to provide "much more robust support for content protection systems" (see digital rights management)...
Recommendation system Collaborativefiltering Content-based filtering Hybrid recommender systems (Collaborative and content-based filtering) Search engine Search...
degradation. Two secondary benefits of the aluminum capping layer include robustness to electrical contacts and the back reflection of emitted light out to...
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