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EUROPAR
1999
Springer
15 years 9 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene
CIDR
2011
266views Algorithms» more  CIDR 2011»
14 years 8 months ago
Consistency in a Stream Warehouse
A stream warehouse is a Data Stream Management System (DSMS) that stores a very long history, e.g. years or decades; or equivalently a data warehouse that is continuously loaded. ...
Lukasz Golab, Theodore Johnson
KDD
2005
ACM
104views Data Mining» more  KDD 2005»
16 years 5 months ago
Mining tree queries in a graph
We present an algorithm for mining tree-shaped patterns in a large graph. Novel about our class of patterns is that they can contain constants, and can contain existential nodes w...
Bart Goethals, Eveline Hoekx, Jan Van den Bussche
IADIS
2008
15 years 6 months ago
Customer Insights from Transactional Database: Database Marketing Case
Marketing databases are currently one of the most important resources in any marketing departments. Regarding their customer knowledge needs many of them had develop their own dat...
Filipe Mota Pinto, Alzira Ascensão Marques,...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 5 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...