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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
16 years 7 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 7 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
209
Voted
KDD
2005
ACM
161views Data Mining» more  KDD 2005»
16 years 7 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
KDD
2003
ACM
99views Data Mining» more  KDD 2003»
16 years 7 months ago
Fragments of order
High-dimensional collections of 0-1 data occur in many applications. The attributes in such data sets are typically considered to be unordered. However, in many cases there is a n...
Aristides Gionis, Teija Kujala, Heikki Mannila
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 7 months ago
Visualized Classification of Multiple Sample Types
The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and re...
Li Zhang, Aidong Zhang, Murali Ramanathan
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