98 search results - page 1 / 20 » Online learning to diversify from implicit feedback |
KDD
2012
ACM
11 years 9 months ago
2012
ACM
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
KDD
2007
ACM
14 years 7 months ago
2007
ACM
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
ECIR
2011
Springer
12 years 10 months ago
2011
Springer
Abstract. As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches...
ICMI
2009
Springer
14 years 1 months ago
2009
Springer
We introduce GaZIR, a gaze-based interface for browsing and searching for images. The system computes on-line predictions of relevance of images based on implicit feedback, and wh...
GROUP
2005
ACM
14 years 4 days ago
2005
ACM
Many virtual communities involve ongoing discussions, with large numbers of users and established, if implicit rules for participation. As new users enter communities like this, b...