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KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 7 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
KDD
2009
ACM
221views Data Mining» more  KDD 2009»
16 years 7 months ago
Migration motif: a spatial - temporal pattern mining approach for financial markets
A recent study by two prominent finance researchers, Fama and French, introduces a new framework for studying risk vs. return: the migration of stocks across size-value portfolio ...
Xiaoxi Du, Ruoming Jin, Liang Ding, Victor E. Lee,...
KDD
2007
ACM
160views Data Mining» more  KDD 2007»
16 years 7 months ago
Show me the money!: deriving the pricing power of product features by mining consumer reviews
The increasing pervasiveness of the Internet has dramatically changed the way that consumers shop for goods. Consumergenerated product reviews have become a valuable source of inf...
Nikolay Archak, Anindya Ghose, Panagiotis G. Ipeir...
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 7 months ago
Practical learning from one-sided feedback
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...
D. Sculley
KDD
2007
ACM
209views Data Mining» more  KDD 2007»
16 years 7 months ago
Temporal causal modeling with graphical granger methods
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
Andrew Arnold, Yan Liu, Naoki Abe
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