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» Phenomenal Data Mining: From Data to Phenomena
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KDD
2009
ACM
143views Data Mining» more  KDD 2009»
16 years 2 months ago
Optimizing web traffic via the media scheduling problem
Website traffic varies through time in consistent and predictable ways, with highest traffic in the middle of the day. When providing media content to visitors, it is important to...
Lars Backstrom, Jon M. Kleinberg, Ravi Kumar
KDD
2007
ACM
190views Data Mining» more  KDD 2007»
16 years 2 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith
ICDM
2006
IEEE
110views Data Mining» more  ICDM 2006»
15 years 8 months ago
Manifold Clustering of Shapes
Shape clustering can significantly facilitate the automatic labeling of objects present in image collections. For example, it could outline the existing groups of pathological ce...
Dragomir Yankov, Eamonn J. Keogh
ICDM
2005
IEEE
185views Data Mining» more  ICDM 2005»
15 years 7 months ago
Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping
The problem of record linkage focuses on determining whether two object descriptions refer to the same underlying entity. Addressing this problem effectively has many practical ap...
Mikhail Bilenko, Sugato Basu, Mehran Sahami
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
15 years 6 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong