Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Mining Modus-operandi Patterns of Swedish Serial Burglaries
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Around 22,000 burglaries are reported to the Swedish police in 2012. It is not only inefficient to analyze these records by human experts, lots of valuable information remains hidden due to weakness of human information processing. Data mining is a promising technique to uncover hidden, unknown and potentially valuable information from large amount of data. The goal of this project is to analyze burglary records and find crime patterns from a burglary dataset by using data mining and machine learning techniques. In this paper from the perspective of data mining I redefine the crime patterns by International Association of Crime Analysts. Then a series of correspondent algorithms and techniques are introduced to mine these patterns. A prototype is implemented to analyze the provided dataset. Crime patterns are identified and visualized in an understandable and user friendly fashion.

Place, publisher, year, edition, pages
2015. , 54 p.
Series
IT, 15073IT
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-265415OAI: oai:DiVA.org:uu-265415DiVA: diva2:865532
Educational program
Master Programme in Computer Science
Supervisors
Examiners
Available from: 2015-10-28 Created: 2015-10-28 Last updated: 2015-10-28Bibliographically approved

Open Access in DiVA

fulltext(1829 kB)307 downloads
File information
File name FULLTEXT01.pdfFile size 1829 kBChecksum SHA-512
d8426662214b805a3621585ed7032b39ee9f06e71e227b6cd2a9a299587be2a105a9f3477fe65880adb2d85d73a5b5be34fca2b1981b65b3932cff1f1fc70963
Type fulltextMimetype application/pdf

By organisation
Department of Information Technology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 307 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 1356 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf