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SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
14 years 9 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal
DMSN
2006
ACM
14 years 3 months ago
Intelligent system monitoring on large clusters
Modern data centers have a large number of components that must be monitored, including servers, switches/routers, and environmental control systems. This paper describes InteMon,...
Jimeng Sun, Evan Hoke, John D. Strunk, Gregory R. ...
KDD
1998
ACM
123views Data Mining» more  KDD 1998»
14 years 1 months ago
Scaling Clustering Algorithms to Large Databases
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Paul S. Bradley, Usama M. Fayyad, Cory Reina
SISAP
2011
IEEE
437views Data Mining» more  SISAP 2011»
12 years 12 months ago
Succinct nearest neighbor search
In this paper we present a novel technique for nearest neighbor searching dubbed neighborhood approximation. The central idea is to divide the database into compact regions repres...
Eric Sadit Tellez, Edgar Chávez, Gonzalo Na...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 9 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...