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Novel applications of Association Rule Mining- Data Stream Mining

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Whole thesis(581.54 KB)

Date

2009

Authors

Supervisor

Pears, Russel

Item type

Thesis

Degree name

Master of Computer and Information Sciences

Journal Title

Journal ISSN

Volume Title

Publisher

Auckland University of Technology

Abstract

From the advent of association rule mining, it has become one of the most researched areas of data exploration schemes. In recent years, implementing association rule mining methods in extracting rules from a continuous flow of voluminous data, known as Data Stream has generated immense interest due to its emerging applications such as network-traffic analysis, sensor-network data analysis. For such typical kinds of application domains, the facility to process such enormous amount of stream data in a single pass is critical.

Description

Keywords

Data stream mining, Association rule mining

Source

DOI

Publisher's version

Rights statement

Permanent link

https://hdl.handle.net/10292/826

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Masters Theses