Non-Linear Correlation Discovery-Based Technique in Data Mining

Author

Liu Bo

Author_Institution

Sch. of Educ. Inf. Technol., South China Normal Univ., Guangzhou

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

107

Lastpage

111

Abstract

In this paper, a novel technique was present for mining complete correlation itemset, named as NLCD(non-linear correlation discovery) from hereon. In the first, it employ the vertical representation of a database, and then to find the direction between the correlative itemsets with fast processing and lots of them through the whole, including many kinds of correlation. Transaction ids of each itemset are mapped and compressed to discrete bool sequence. Lastly it was evaluated the algorithm against algorithms LCD using a variety of data sets with short and long frequent patterns. Experimental report showed that the NLCD algorithm outperforms.

Keywords

correlation methods; data compression; data mining; transaction processing; data compression; data mining; discrete bool sequence; nonlinear correlation discovery; transactional data; Algorithm design and analysis; Association rules; Data mining; Information analysis; Information technology; Intrusion detection; Itemsets; Logic; Statistics; Transaction databases; correlation discovery; data mining; non-linear;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3505-0

Type

conf

DOI

10.1109/IITA.Workshops.2008.30

Filename

4731892