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ICDM
2007
IEEE
118views Data Mining» more  ICDM 2007»
14 years 4 months ago
Subgraph Support in a Single Large Graph
—Defining the support (or frequency) of a subgraph is trivial when a database of graphs is given: it is simply the number of graphs in the database that contain the subgraph. Ho...
Mathias Fiedler, Christian Borgelt
EUROPAR
1999
Springer
14 years 2 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
KDD
1994
ACM
125views Data Mining» more  KDD 1994»
14 years 2 months ago
Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth
This paper discusses the problem of knowledge discovery in image databases with particular focus on the issues which arise when absolute ground truth is not available. It is often...
Padhraic Smyth, Michael C. Burl, Usama M. Fayyad, ...
ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
14 years 4 months ago
Finding Maximal Fully-Correlated Itemsets in Large Databases
—Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. Much previous research focuses on finding ...
Lian Duan, William Nick Street
ICDT
2001
ACM
124views Database» more  ICDT 2001»
14 years 2 months ago
Mining for Empty Rectangles in Large Data Sets
Abstract. Many data mining approaches focus on the discovery of similar (and frequent) data values in large data sets. We present an alternative, but complementary approach in whic...
Jeff Edmonds, Jarek Gryz, Dongming Liang, Ren&eacu...