Graph drawing by force-directed placement
Software—Practice & Experience
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Evaluation of Item-Based Top-N Recommendation Algorithms
Proceedings of the tenth international conference on Information and knowledge management
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
MovieLens unplugged: experiences with an occasionally connected recommender system
Proceedings of the 8th international conference on Intelligent user interfaces
Improving Case-Based Recommendation: A Collaborative Filtering Approach
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Information Visualization: Perception for Design
Information Visualization: Perception for Design
Vizster: Visualizing Online Social Networks
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
Visual exploration of multivariate graphs
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
TreePlus: Interactive Exploration of Networks with Enhanced Tree Layouts
IEEE Transactions on Visualization and Computer Graphics
Don't look stupid: avoiding pitfalls when recommending research papers
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Your place or mine?: visualization as a community component
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
PeerChooser: visual interactive recommendation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A visual interface for critiquing-based recommender systems
Proceedings of the 9th ACM conference on Electronic commerce
User interactions in social networks and their implications
Proceedings of the 4th ACM European conference on Computer systems
WiGis: a framework for scalable web-based interactive graph visualizations
GD'09 Proceedings of the 17th international conference on Graph Drawing
Scalable, versatile and simple constrained graph layout
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
SFViz: interest-based friends exploration and recommendation in social networks
Proceedings of the 2011 Visual Information Communication - International Symposium
TopicNets: Visual Analysis of Large Text Corpora with Topic Modeling
ACM Transactions on Intelligent Systems and Technology (TIST)
Bell Labs Technical Journal
Visual recommendations for network navigation
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Visualizing recommendations to support exploration, transparency and controllability
Proceedings of the 2013 international conference on Intelligent user interfaces
A field study of a visual controllable talk recommender
Proceedings of the 2013 Chilean Conference on Human - Computer Interaction
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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We present SmallWorlds, a visual interactive graph-based interface that allows users to specify, refine and build item-preference profiles in a variety of domains. The interface facilitates expressions of taste through simple graph interactions and these preferences are used to compute personalized, fully transparent item recommendations for a target user. Predictions are based on a collaborative analysis of preference data from a user's direct peer group on a social network. We find that in addition to receiving transparent and accurate item recommendations, users also learn a wealth of information about the preferences of their peers through interaction with our visualization. Such information is not easily discoverable in traditional text based interfaces. A detailed analysis of our design choices for visual layout, interaction and prediction techniques is presented. Our evaluations discuss results from a user study in which SmallWorlds was deployed as an interactive recommender system on Facebook.