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

41

Abstract

In this thesis, we will use various techniques from data mining to draw interesting results from a set of structured data on personal privacy information. In particular, the well-known, Apriori Algorithm will be used to find frequent item sets and association rules in this data. This process has been shown to be effective in predicting the presence of one type of data when other data is present in other data mining applications; The thesis will also include a detailed analysis of rules generated by the algorithm and their natural interpretations.

Keywords

Algorithms; Analyzing; Applying; Apriori; Association; Data; Produced; Rules; Structured

Controlled Subject

Computer science

File Format

pdf

File Size

1116.16 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/emjr-981x


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