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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 4 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
KDD
2006
ACM
173views Data Mining» more  KDD 2006»
16 years 4 months ago
Robust information-theoretic clustering
How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clu...
Christian Böhm, Christos Faloutsos, Claudia P...
APN
2007
Springer
15 years 10 months ago
ProM 4.0: Comprehensive Support for Real Process Analysis
This tool paper describes the functionality of ProM. Version 4.0 of ProM has been released at the end of 2006 and this version reflects recent achievements in process mining. Proc...
Wil M. P. van der Aalst, Boudewijn F. van Dongen, ...
VLDB
2005
ACM
136views Database» more  VLDB 2005»
15 years 9 months ago
On k-Anonymity and the Curse of Dimensionality
In recent years, the wide availability of personal data has made the problem of privacy preserving data mining an important one. A number of methods have recently been proposed fo...
Charu C. Aggarwal
PAKDD
2011
ACM
419views Data Mining» more  PAKDD 2011»
14 years 6 months ago
DISC: Data-Intensive Similarity Measure for Categorical Data
Abstract. The concept of similarity is fundamentally important in almost every scientific field. Clustering, distance-based outlier detection, classification, regression and sea...
Aditya Desai, Himanshu Singh, Vikram Pudi