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» Practical Preference Relations for Large Data Sets
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ICDM
2005
IEEE
168views Data Mining» more  ICDM 2005»
14 years 2 months ago
A Scalable Collaborative Filtering Framework Based on Co-Clustering
Collaborative filtering-based recommender systems, which automatically predict preferred products of a user using known preferences of other users, have become extremely popular ...
Thomas George, Srujana Merugu
WWW
2009
ACM
14 years 9 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel
PAMI
2010
164views more  PAMI 2010»
13 years 6 months ago
Large-Scale Discovery of Spatially Related Images
— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
Ondrej Chum, Jiri Matas
ICDM
2008
IEEE
190views Data Mining» more  ICDM 2008»
14 years 2 months ago
Simultaneous Co-segmentation and Predictive Modeling for Large, Temporal Marketing Data
Several marketing problems involve prediction of customer purchase behavior and forecasting future preferences. We consider predictive modeling of large scale, bi-modal or multimo...
Meghana Deodhar, Joydeep Ghosh
PVLDB
2008
182views more  PVLDB 2008»
13 years 7 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...