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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 2 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
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 2 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
KDD
2006
ACM
173views Data Mining» more  KDD 2006»
16 years 2 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...
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 2 months ago
Spatial scan statistics: approximations and performance study
Spatial scan statistics are used to determine hotspots in spatial data, and are widely used in epidemiology and biosurveillance. In recent years, there has been much effort invest...
Deepak Agarwal, Andrew McGregor, Jeff M. Phillips,...
CHI
2005
ACM
16 years 2 months ago
The rotating compass: a novel interaction technique for mobile navigation
In current mobile navigation systems users receive the navigational instructions on a visual display or by descriptive audio. The mapping between the provided navigation informati...
Enrico Rukzio, Albrecht Schmidt, Antonio Krüg...