AAU-ETD AAU-ETD
 

Addis Ababa University Libraries Electronic Thesis and Dissertations: AAU-ETD! >
Faculty of Informatics >
Thesis - Information Science >

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1030

Title: APPLICATION OF KDD ON CRIME DATA TO SUPPORT THE ADVOCACY AND AWARENESS RAISING PROGRAM OF FORUM ON STREET CHILDREN ETHIOPIA
Authors: WOLDEKIDAN, KIFLE
Advisors: Dr. Gashaw Kebede
Ato Shegaw Anagaw
Copyright: 2003
Date Added: 9-May-2008
Publisher: Addis Ababa University
Abstract: This thesis work gives an account of the process followed to determine the application of KDD to support the advocacy and awareness raising program of FSCE and Addis Ababa Police Commission, and the potential of a data mining learning scheme to discover regularities that underlie the crime dataset. The KDD process as described by Fayyad, Piatetsky-Shapiro and Gregory (1996) that consists of five major phases, namely understanding of the problem domain, data selection, data preprocessing, data mining, and discussion and interpretation was adopted. The discovery task was run on the crime database that consists of 10,878 records/tuples in 17 tables describing a total of 25 attributes. Association rule mining, an exploratory data mining technique was applied to accomplish the goal of the research. To this effect, the Apriori algorithm, which is an implementation of the Association rule in the Weka software, was used. The KDD process can be applied on the crime database to good effect since it can result in rules that can serve as input for the advocacy and awareness raising program. On the basis of subjective (opinions of domain experts) and objective (support and confidence) measures of interestingness, a number of rules having practical relevance or that can add to the current knowledge in the problem domain were identified.
Description: A thesis submitted to the School of Graduate Studies of Addis Ababa University in partial fulfillment of the requirements for the Degree of Master of Science in Information Science.
URI: http://hdl.handle.net/123456789/1030
Appears in:Thesis - Information Science

Files in This Item:

File Description SizeFormat
WOLDEKIDAN KIFLE.pdf668.05 kBAdobe PDFView/Open

Items in the AAUL Digital Library are protected by copyright, with all rights reserved, unless otherwise indicated.

 

  Last updated: May 2010. Copyright © Addis Ababa University Libraries - Feedback