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» Clustering Transactions Using Large Items
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JCP
2006
173views more  JCP 2006»
14 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»
14 years 9 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
15 years 1 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»
15 years 9 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»
14 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. ...