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» Techniques of Cluster Algorithms in Data Mining
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SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
16 years 6 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
15 years 11 months ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel
IPPS
1998
IEEE
15 years 10 months ago
High Performance Data Mining Using Data Cubes on Parallel Computers
On-Line Analytical Processing techniques are used for data analysis and decision support systems. The multidimensionality of the underlying data is well represented by multidimens...
Sanjay Goil, Alok N. Choudhary
INTERNET
2006
157views more  INTERNET 2006»
15 years 6 months ago
Distributed Data Mining in Peer-to-Peer Networks
Distributed data mining deals with the problem of data analysis in environments with distributed data, computing nodes, and users. Peer-to-peer computing is emerging as a new dist...
Souptik Datta, Kanishka Bhaduri, Chris Giannella, ...
APCHI
2004
IEEE
15 years 10 months ago
Evolutionary Approaches to Visualisation and Knowledge Discovery
Haiku is a data mining system which combines the best properties of human and machine discovery. An self organising visualisation system is coupled with a genetic algorithm to prov...
Russell Beale, Andy Pryke, Robert J. Hendley