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» Clustering Transactions Using Large Items
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JCP
2006
173views more  JCP 2006»
13 years 9 months ago
Database Intrusion Detection using Weighted Sequence Mining
Data mining is widely used to identify interesting, potentially useful and understandable patterns from a large data repository. With many organizations focusing on webbased on-lin...
Abhinav Srivastava, Shamik Sural, Arun K. Majumdar
BMCBI
2010
139views more  BMCBI 2010»
13 years 10 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
IJCNN
2000
IEEE
14 years 2 months ago
Fuzzy Clustering Algorithm Extracting Principal Components Independent of Subsidiary Variables
Fuzzy c-varieties (FCV) is one of the clustering algorithms in which the prototypes are multi-dimensional linear varieties. The linear varieties are represented by some local prin...
Chi-Hyon Oh, Hirokazu Komatsu, Katsuhiro Honda, Hi...
EDBT
2008
ACM
156views Database» more  EDBT 2008»
14 years 10 months ago
Online recovery in cluster databases
Cluster based replication solutions are an attractive mechanism to provide both high-availability and scalability for the database backend within the multi-tier information system...
WeiBin Liang, Bettina Kemme
DKE
2007
119views more  DKE 2007»
13 years 9 months ago
Association rules mining using heavy itemsets
A well-known problem that limits the practical usage of association rule mining algorithms is the extremely large number of rules generated. Such a large number of rules makes the...
Girish Keshav Palshikar, Mandar S. Kale, Manoj M. ...