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SDM
2003
SIAM
134views Data Mining» more  SDM 2003»
15 years 8 months ago
Hierarchical Document Clustering using Frequent Itemsets
A major challenge in document clustering is the extremely high dimensionality. For example, the vocabulary for a document set can easily be thousands of words. On the other hand, ...
Benjamin C. M. Fung, Ke Wang, Martin Ester
KDD
2004
ACM
118views Data Mining» more  KDD 2004»
16 years 7 months ago
Parallel computation of high dimensional robust correlation and covariance matrices
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
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
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 8 months ago
Clustering from Constraint Graphs
In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...
Ari Freund, Dan Pelleg, Yossi Richter
CAEPIA
2003
Springer
15 years 12 months ago
Rotation-Based Ensembles
A new method for ensemble generation is presented. It is based on grouping the attributes in dierent subgroups, and to apply, for each group, an axis rotation, using Principal Com...
Juan José Rodríguez, Carlos J. Alons...