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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 3 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
154
Voted
KDD
2007
ACM
201views Data Mining» more  KDD 2007»
16 years 3 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...
129
Voted
KDD
2007
ACM
169views Data Mining» more  KDD 2007»
16 years 3 months ago
Exploiting underrepresented query aspects for automatic query expansion
Users attempt to express their search goals through web search queries. When a search goal has multiple components or aspects, documents that represent all the aspects are likely ...
Daniel Crabtree, Peter Andreae, Xiaoying Gao
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
16 years 3 months ago
Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis
To unravel the concept structure and dynamics of the bioinformatics field, we analyze a set of 7401 publications from the Web of Science and MEDLINE databases, publication years 1...
Bart De Moor, Frizo A. L. Janssens, Wolfgang Gl&au...
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 3 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