Award Date

1-1-2005

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Committee Member

Kazem Taghva

Number of Pages

63

Abstract

Data mining represents the process of extracting interesting and previously unknown knowledge from data. In this thesis we address the important data mining problem of discovering association rules. An association rule expresses the dependence of a set of attribute-value pairs, also called items, upon another set of items; We also report on various implementation techniques for the well-known Apriori Algorithm and their time complexity.

Keywords

Algorithms; Analysis; Apriori; Data; Implementation; Mining

Controlled Subject

Computer science

File Format

pdf

File Size

1239.04 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

If you are the rightful copyright holder of this dissertation or thesis and wish to have the full text removed from Digital Scholarship@UNLV, please submit a request to digitalscholarship@unlv.edu and include clear identification of the work, preferably with URL.

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Download


COinS