GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
The role of transparency in recommender systems
CHI '02 Extended Abstracts on Human Factors in Computing Systems
MovieLens unplugged: experiences with an occasionally connected recommender system
Proceedings of the 8th international conference on Intelligent user interfaces
IEEE Transactions on Visualization and Computer Graphics
Proceedings of the 10th international conference on Intelligent user interfaces
Rush: repeated recommendations on mobile devices
Proceedings of the 15th international conference on Intelligent user interfaces
Editorial: Data mining for understanding user needs
ACM Transactions on Computer-Human Interaction (TOCHI)
Information Sciences: an International Journal
Who is talking about what: social map-based recommendation for content-centric social websites
Proceedings of the fourth ACM conference on Recommender systems
SFViz: interest-based friends exploration and recommendation in social networks
Proceedings of the 2011 Visual Information Communication - International Symposium
Who is Doing What and When: Social Map-Based Recommendation for Content-Centric Social Web Sites
ACM Transactions on Intelligent Systems and Technology (TIST)
TasteWeights: a visual interactive hybrid recommender system
Proceedings of the sixth ACM conference on Recommender systems
Inspectability and control in social recommenders
Proceedings of the sixth ACM conference on Recommender systems
Beyond lists: studying the effect of different recommendation visualizations
Proceedings of the sixth ACM conference on Recommender systems
Smallworlds: visualizing social recommendations
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Visualizing recommendations to support exploration, transparency and controllability
Proceedings of the 2013 international conference on Intelligent user interfaces
Supporting exploratory people search: a study of factor transparency and user control
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
See what you want to see: visual user-driven approach for hybrid recommendation
Proceedings of the 19th international conference on Intelligent User Interfaces
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Collaborative filtering (CF) has been successfully deployed over the years to compute predictions on items based on a user's correlation with a set of peers. The black-box nature of most CF applications leave the user wondering how the system arrived at its recommendation. This note introduces PeerChooser, a collaborative recommender system with an interactive graphical explanation interface. Users are provided with a visual explanation of the CF process and opportunity to manipulate their neighborhood at varying levels of granularity to reflect aspects of their current requirements. In this manner we overcome the problem of redundant profile information in CF systems, in addition to providing an explanation interface. Our layout algorithm produces an exact, noiseless graph representation of the underlying correlations between users. PeerChooser's prediction component uses this graph directly to yield the same results as the benchmark. User's then improve on these predictions by tweaking the graph to their current requirements. We present a user-survey in which PeerChooser compares favorably against a benchmark CF algorithm.