Techniques for improving clustering and association rules mining from very large transactional databases

Techniques for improving clustering and association rules mining from very large transactional databases

Clustering and association rules mining are two core data mining tasks that have been actively studied by data mining community for nearly two decades. Though many clustering and association rules mining algorithms have been developed, no algorithm is better than others on all aspects, such as accur...

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Bibliographic Details
Main Author: Li, Yanrong
Format: Thesis
Language:English
Published: Curtin University 2009
Subjects:
incremental clustering algorithm (INCLUS)
static stored databases
data mining community
clustering and association rules mining
data streams
mining algorithms
transactional databases
core data mining tasks
sampling techniques
Online Access:http://hdl.handle.net/20.500.11937/907

Internet

http://hdl.handle.net/20.500.11937/907

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