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» Discovering Case Knowledge Using Data Mining
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KDD
2006
ACM
157views Data Mining» more  KDD 2006»
16 years 1 months ago
Using structure indices for efficient approximation of network properties
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...
Matthew J. Rattigan, Marc Maier, David Jensen
131
Voted
ICML
2001
IEEE
16 years 1 months ago
Constrained K-means Clustering with Background Knowledge
Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data in...
Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan ...
92
Voted
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
16 years 1 months ago
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Defining outliers by their distance to neighboring examples is a popular approach to finding unusual examples in a data set. Recently, much work has been conducted with the goal o...
Stephen D. Bay, Mark Schwabacher
MLG
2007
Springer
15 years 6 months ago
Improving Frequent Subgraph Mining in the Presence of Symmetry
While recent algorithms for mining the frequent subgraphs of a database are efficient in the general case, these algorithms tend to do poorly on databases that have a few or no la...
Christian Desrosiers, Philippe Galinier, Pierre Ha...
213
Voted
ICDE
2008
IEEE
141views Database» more  ICDE 2008»
16 years 2 months ago
A General Framework for Fast Co-clustering on Large Datasets Using Matrix Decomposition
Abstract-- Simultaneously clustering columns and rows (coclustering) of large data matrix is an important problem with wide applications, such as document mining, microarray analys...
Feng Pan, Xiang Zhang, Wei Wang 0010