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» Experimental perspectives on learning from imbalanced data
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KDD
2012
ACM
254views Data Mining» more  KDD 2012»
13 years 14 days ago
Playlist prediction via metric embedding
Digital storage of personal music collections and cloud-based music services (e.g. Pandora, Spotify) have fundamentally changed how music is consumed. In particular, automatically...
Shuo Chen, Josh L. Moore, Douglas Turnbull, Thorst...
ICDM
2007
IEEE
183views Data Mining» more  ICDM 2007»
15 years 4 months ago
Depth-Based Novelty Detection and Its Application to Taxonomic Research
It is estimated that less than 10 percent of the world’s species have been described, yet species are being lost daily due to human destruction of natural habitats. The job of d...
Yixin Chen, Henry L. Bart Jr., Xin Dang, Hanxiang ...
KDD
2006
ACM
183views Data Mining» more  KDD 2006»
15 years 10 months ago
Discovering interesting patterns through user's interactive feedback
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Dong Xin, Xuehua Shen, Qiaozhu Mei, Jiawei Han
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
15 years 10 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
15 years 4 months ago
Automatic Construction of N-ary Tree Based Taxonomies
Hierarchies are an intuitive and effective organization paradigm for data. Of late there has been considerable research on automatically learning hierarchical organizations of dat...
Kunal Punera, Suju Rajan, Joydeep Ghosh