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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
16 years 6 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
KDD
2007
ACM
136views Data Mining» more  KDD 2007»
16 years 6 months ago
Information genealogy: uncovering the flow of ideas in non-hyperlinked document databases
We now have incrementally-grown databases of text documents ranging back for over a decade in areas ranging from personal email, to news-articles and conference proceedings. While...
Benyah Shaparenko, Thorsten Joachims
KDD
2007
ACM
209views Data Mining» more  KDD 2007»
16 years 6 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
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
16 years 6 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
KDD
2005
ACM
218views Data Mining» more  KDD 2005»
16 years 6 months ago
A maximum entropy web recommendation system: combining collaborative and content features
Web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. Web usage mining techniques are used to ext...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
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