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» Putting Users in Control of their Recommendations
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RECSYS
2009
ACM
15 years 4 months ago
Increasing engagement through early recommender intervention
Social network sites rely on the contributions of their members to create a lively and enjoyable space. Recent research has focused on using personalization and recommender techno...
Jill Freyne, Michal Jacovi, Ido Guy, Werner Geyer
SDM
2007
SIAM
106views Data Mining» more  SDM 2007»
14 years 11 months ago
Performance of Recommendation Systems in Dynamic Streaming Environments
In this paper, we study the behavior of collaborative filtering based recommendations under evolving user profile scenarios. We propose a systematic validation methodology that ...
Olfa Nasraoui, Jeff Cerwinske, Carlos Rojas, Fabio...
RECSYS
2009
ACM
15 years 4 months ago
A partial-order based active cache for recommender systems
Recommender systems aim to substantially reduce information overload by suggesting lists of similar items that users may find interesting. Caching has been a useful technique for...
Umar Qasim, Vincent Oria, Yi-fang Brook Wu, Michae...
ICCBR
2010
Springer
15 years 2 months ago
Case-Based Plan Diversity
The concept of diversity was successfully introduced for recommender-systems. By displaying results that are not only similar to a target problem but also diverse among themselves,...
Alexandra Coman, Héctor Muñoz-Avila
RECSYS
2010
ACM
14 years 10 months ago
Nantonac collaborative filtering: a model-based approach
A recommender system has to collect users' preference data. To collect such data, rating or scoring methods that use rating scales, such as good-fair-poor or a five-point-sca...
Toshihiro Kamishima, Shotaro Akaho