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» Improving Case-Based Recommendations Using Implicit Feedback
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CIKM
2010
Springer
13 years 6 months ago
Collaborative future event recommendation
We demonstrate a method for collaborative ranking of future events. Previous work on recommender systems typically relies on feedback on a particular item, such as a movie, and ge...
Einat Minkov, Ben Charrow, Jonathan Ledlie, Seth J...
SGAI
2004
Springer
14 years 25 days ago
Incremental Critiquing
Conversational recommender systems guide users through a product space, alternatively making concrete product suggestions and eliciting the user’s feedback. Critiquing is a comm...
James Reilly, Kevin McCarthy, Lorraine McGinty, Ba...
SIGIR
2010
ACM
13 years 11 months ago
Interactive retrieval based on faceted feedback
Motivated by the commonly used faceted search interface in e-commerce, this paper investigates interactive relevance feedback mechanism based on faceted document metadata. In this...
Lanbo Zhang, Yi Zhang
RECSYS
2009
ACM
14 years 2 months ago
TagiCoFi: tag informed collaborative filtering
Besides the rating information, an increasing number of modern recommender systems also allow the users to add personalized tags to the items. Such tagging information may provide...
Yi Zhen, Wu-Jun Li, Dit-Yan Yeung
ICDM
2010
IEEE
172views Data Mining» more  ICDM 2010»
13 years 5 months ago
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
Cold-start scenarios in recommender systems are situations in which no prior events, like ratings or clicks, are known for certain users or items. To compute predictions in such ca...
Zeno Gantner, Lucas Drumond, Christoph Freudenthal...