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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
2007
ACM
201views Data Mining» more  KDD 2007»
16 years 4 months ago
Structural and temporal analysis of the blogosphere through community factorization
The blogosphere has unique structural and temporal properties since blogs are typically used as communication media among human individuals. In this paper, we propose a novel tech...
Yun Chi, Shenghuo Zhu, Xiaodan Song, Jun'ichi Tate...
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 4 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
16 years 4 months ago
Mining optimal decision trees from itemset lattices
We present DL8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. Because the discovery of optimal...
Élisa Fromont, Siegfried Nijssen
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 4 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...