Title :
Analysis and implementation of association rule mining
Author :
Banu, R.K. ; Ravanan, R. ; Gopal, J.
Author_Institution :
Master of Comput. Applic., Loyola Inst. of Technol., Chennai, India
Abstract :
Data mining Build models of the world (regression, decision trees, neural networks, association rules, fuzzy systems,..) from data that represent snippets of information about the world. Use these models to understand and discover patterns of interest that may provide knowledge deployable in improving business processes. The non-trivial extraction of novel, implicit, and actionable knowledge from large databases and in a timely manner. The APriori Data Mining Algorithm is used to create association rules from sets of items. The algorithm finds patterns of items Algorithm uses knowledge from previous iteration phase to produce frequent itemsets that are frequently associated together. A confidence measure is created for each rule generated from the frequent itemsets.
Keywords :
data mining; apriori data mining algorithm; association rule mining; business processes; Algorithm design and analysis; Association rules; Image processing; Itemsets; Spatial databases; Apriori Algorithm; Association rules; Data mining;
Conference_Titel :
Signal and Image Processing (ICSIP), 2010 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4244-8595-6
DOI :
10.1109/ICSIP.2010.5697521