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CSCW
1998
ACM
13 years 8 months ago
Using Filtering Agents to Improve Prediction Quality in the GroupLens Research Collaborative Filtering System
Collaborative filtering systems help address information overload by using the opinions of users in a community to make personal recommendations for documents to each user. Many c...
Badrul M. Sarwar, Joseph A. Konstan, Al Borchers, ...
CSCW
2000
ACM
13 years 8 months ago
Explaining collaborative filtering recommendations
Automated collaborative filtering (ACF) systems predict a person’s affinity for items or information by connecting that person’s recorded interests with the recorded interests...
Jonathan L. Herlocker, Joseph A. Konstan, John Rie...
RECSYS
2009
ACM
13 years 10 months ago
Ordering innovators and laggards for product categorization and recommendation
Different buyers exhibit different purchasing behaviors. Some rush to purchase new products while others tend to be more cautious, waiting for reviews from people they trust. In...
Sarah K. Tyler, Shenghuo Zhu, Yun Chi, Yi Zhang
CHI
2007
ACM
13 years 8 months ago
Follow the reader: filtering comments on slashdot
Large-scale online communities need to manage the tension between critical mass and information overload. Slashdot is a news and discussion site that has used comment rating to al...
Cliff Lampe, Erik W. Johnston, Paul Resnick
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 6 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...