Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/134206
Title: Discovery and utilization of quality Association rules in frequent Datasets
Researcher: Balajiraja N
Guide(s): Balakrishnan G
Keywords: Datasets
quality Association
Science and humanities
University: Anna University
Completed Date: 01/09/2015
Abstract: Data mining is an emerging interdisciplinary research area newlineprimarily focuses on the development of new approaches to explore data in newlinevarious contexts Among several approaches Association rule mining is the newlineprinciple technique predominantly used in data mining at multi context data newlinelevel It frequently discovers the interesting relationship in a large newlinetransactional datasets Over the period of two decades it evolved to a newlinesignificant level in this domain and still invents new approaches continuingly newlineSeveral algorithms related to association rule mining are now newlineavailable However most of the algorithms utilize huge volume of memory newlinediscover irrelevant relationships and ended up with large count of redundant newlineassociation rules To overcome the above said issues in the existing newlinealgorithms and to increase the performance of association rule mining, newlinevarious approaches are proposed in this research newline newline
Pagination: xxiii, 182p.
URI: http://hdl.handle.net/10603/134206
Appears in Departments:Faculty of Science and Humanities

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09_chapter 2.pdf293.17 kBAdobe PDFView/Open
10_chapter 3.pdf13.67 kBAdobe PDFView/Open
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12_chapter 5.pdf386.83 kBAdobe PDFView/Open
13_chapter 6.pdf714.71 kBAdobe PDFView/Open
14_chapter 7.pdf36.48 kBAdobe PDFView/Open
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