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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 6 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
SIGMOD
2007
ACM
413views Database» more  SIGMOD 2007»
16 years 6 months ago
Effective keyword-based selection of relational databases
The wide popularity of free-and-easy keyword based searches over World Wide Web has fueled the demand for incorporating keyword-based search over structured databases. However, mo...
Bei Yu, Guoliang Li, Karen R. Sollins, Anthony K. ...
SIGMOD
1998
ACM
117views Database» more  SIGMOD 1998»
15 years 10 months ago
The Pyramid-Technique: Towards Breaking the Curse of Dimensionality
In this paper, we propose the Pyramid-Technique, a new indexing method for high-dimensional data spaces. The PyramidTechnique is highly adapted to range query processing using the...
Stefan Berchtold, Christian Böhm, Hans-Peter ...
ISCI
2006
145views more  ISCI 2006»
15 years 6 months ago
Processing count queries over event streams at multiple time granularities
Management and analysis of streaming data has become crucial with its applications in web, sensor data, network traffic data, and stock market. Data streams consist of mostly nume...
Aykut Ünal, Yücel Saygin, Özgü...
KDD
2012
ACM
194views Data Mining» more  KDD 2012»
13 years 9 months ago
A sparsity-inducing formulation for evolutionary co-clustering
Traditional co-clustering methods identify block structures from static data matrices. However, the data matrices in many applications are dynamic; that is, they evolve smoothly o...
Shuiwang Ji, Wenlu Zhang, Jun Liu