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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
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| 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
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