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EDBT
2008
ACM
138views Database» more  EDBT 2008»
14 years 7 months ago
Mine your own business, mine others' news!
Major media companies such as The Financial Times, the Wall Street Journal or Reuters generate huge amounts of textual news data on a daily basis. Mining frequent patterns in this...
Boualem Benatallah, Guillaume Raschia, Noureddine ...
KDD
1998
ACM
123views Data Mining» more  KDD 1998»
13 years 12 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
SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
14 years 4 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,...
CCGRID
2010
IEEE
13 years 8 months ago
High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...
Jong Youl Choi, Seung-Hee Bae, Xiaohong Qiu, Geoff...
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
14 years 1 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez