IDEAS home Printed from https://ideas.repec.org/a/igg/jdwm00/v2y2006i1p50-80.html
   My bibliography  Save this article

An Approach to Mining Crime Patterns

Author

Listed:
  • Sikha Bagui

    (The University of West Florida, USA)

Abstract

This paper presents a knowledge discovery effort to retrieve meaningful information about crime from a U.S. state database. The raw data were preprocessed, and data cubes were created using Structured Query Language (SQL). The data cubes then were used in deriving quantitative generalizations and for further analysis of the data. An entropy-based attribute relevance study was undertaken to determine the relevant attributes. A machine learning software called WEKA was used for mining association rules, developing a decision tree, and clustering. SOM was used to view multidimensional clusters on a regular two-dimensional grid.

Suggested Citation

  • Sikha Bagui, 2006. "An Approach to Mining Crime Patterns," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 2(1), pages 50-80, January.
    • Handle: RePEc:igg:jdwm00:v:2:y:2006:i:1:p:50-80
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jdwm.2006010103
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Steven J. Jurek & Anthony Scime, 2014. "Achieving Democratic Leadership: A Data-Mined Prescription," Social Science Quarterly, Southwestern Social Science Association, vol. 95(1), pages 97-110, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jdwm00:v:2:y:2006:i:1:p:50-80. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.