DocumentCode :
579918
Title :
An Efficient Technique on Cluster Based Master Slave Architecture Design
Author :
Saxena, Neha ; Bhargava, Niket ; Mahor, Urmila ; Dixit, Nitin
Author_Institution :
M.Tech (C.S.E.), B.I.S.T., Bhopal, India
fYear :
2012
fDate :
3-5 Nov. 2012
Firstpage :
561
Lastpage :
565
Abstract :
We are in an age repeatedly referred to the information age. In this age, because we suppose that information leads to power and achievement, and credit to sophisticated techniques such as computers, satellites etc. we include collecting large amount of information similar to business transaction, scientific data, medical data satellite data, surveillance video & pictures world wide web and many more. With the enormous amount of data stored in files, data base and this technique hold large amount of data is called data mining. Data mining is the method of extracting valuable information from the enormous amount of data saved in the database and files. At that time basically two important reasons that are used in data mining. First our capacity to accumulate and store the large amount of data is fast increase day by day, and second but the most imperative basis is the need to turn such data into useful information and knowledge. Association rule mining is a vital procedure to find out hidden interaction with items in the transaction. This paper describes new technique cluster based Master-Slave architecture. It uses Hybrid technique, the grouping of bottom up and top down technique for search repetitive item sets. It reduces the time in use to get out the support count of the item sets. The Prime number show present offers the give for verify rules and provides decrease in the data complexity.
Keywords :
data mining; pattern clustering; World Wide Web; business transaction; cluster based master slave architecture design; data complexity; data mining; efficient technique; medical data satellite data; scientific data; video surveillance; Algorithm design and analysis; Association rules; Clustering algorithms; Itemsets; Partitioning algorithms; Association rule mining; database; master-slave;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on
Conference_Location :
Mathura
Print_ISBN :
978-1-4673-2981-1
Type :
conf
DOI :
10.1109/CICN.2012.44
Filename :
6375176
Link To Document :
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