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KDD
1998
ACM
123views Data Mining» more  KDD 1998»
15 years 2 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
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
15 years 4 months ago
A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks
This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining...
Kanishka Bhaduri, Ashok N. Srivastava
SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
15 years 7 months ago
GAD: General Activity Detection for Fast Clustering on Large Data.
In this paper, we propose GAD (General Activity Detection) for fast clustering on large scale data. Within this framework we design a set of algorithms for different scenarios: (...
Jiawei Han, Liangliang Cao, Sangkyum Kim, Xin Jin,...
MSR
2006
ACM
15 years 3 months ago
Concern based mining of heterogeneous software repositories
In the current trend of software engineering, software systems are viewed as clusters of overlapping structures representing various concerns, covering heterogeneous artifacts lik...
Imed Hammouda, Kai Koskimies
KI
2002
Springer
14 years 9 months ago
Employing Text Mining for Semantic Tagging in DIAsDEM
Both public and private organizations have been accumulating large volumes of electronically available text documents for the past years. However, to turn text archives into profi...
Karsten Winkler, Myra Spiliopoulou