Utvärdering av temporala analysmetoder inom brottskategorin bostadsinbrott

Context. In year 2013 the number of reported residential burglariesin Sweden was 21000, where only 4-5 percent of those actuallygot solved [1]. The Swedish police is trying to improve their way ofworking to increase the number of solved burglaries, this by structuringthe data collection and analysin...

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Main Author: Svenhag, Olle
Format: Others
Language:Swedish
Published: Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik 2015
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:bth-10476
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spelling ndltd-UPSALLA1-oai-DiVA.org-bth-104762018-01-12T05:09:59ZUtvärdering av temporala analysmetoder inom brottskategorin bostadsinbrottsweSvenhag, OlleBlekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik2015Temporal analysisAoristicanalysis methodsresidential burglaries.Computer SciencesDatavetenskap (datalogi)Context. In year 2013 the number of reported residential burglariesin Sweden was 21000, where only 4-5 percent of those actuallygot solved [1]. The Swedish police is trying to improve their way ofworking to increase the number of solved burglaries, this by structuringthe data collection and analysing with computer science methods.Temporal analysis is the key to gure out when crime actually takesplace. Objectives. This thesis study ve dierent methods for analysingthe temporal data of residential burglaries. The temporal analysis isperformed on three time spans: time of day, day of the week and dayof the month. The objective is to evaluate the ve methods in thethree time spans and decide which method is the most suitable foreach of them. Methods. This study includes three experiments testing all ve methodson the three time spans. The experiments focus on comparing theobserved data against the data of burglaries with a known specictime of the crime. In order to test the performance of each method aChi-squared goodness-of-t test was used, as well as a visual comparisonof the produced plots. Results. The results showed that the Aoristic-method was the mostsuitable method to use when analysing temporal data of residentialburglars, if looking at the time of day, day of the week and day ofthe month. Using the methods we also generated plots of the threetemporal distributions, with an R script. Conclusions. We concluded that using the Aoristic-method is themost suitable method to use to generate plots from the temporal data.We also concluded that using this script with the Aoristic-method togenerate plots, would make it possible for the police to resource allocationaccording to when burglaries actually take place. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:bth-10476application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language Swedish
format Others
sources NDLTD
topic Temporal analysis
Aoristic
analysis methods
residential burglaries.
Computer Sciences
Datavetenskap (datalogi)
spellingShingle Temporal analysis
Aoristic
analysis methods
residential burglaries.
Computer Sciences
Datavetenskap (datalogi)
Svenhag, Olle
Utvärdering av temporala analysmetoder inom brottskategorin bostadsinbrott
description Context. In year 2013 the number of reported residential burglariesin Sweden was 21000, where only 4-5 percent of those actuallygot solved [1]. The Swedish police is trying to improve their way ofworking to increase the number of solved burglaries, this by structuringthe data collection and analysing with computer science methods.Temporal analysis is the key to gure out when crime actually takesplace. Objectives. This thesis study ve dierent methods for analysingthe temporal data of residential burglaries. The temporal analysis isperformed on three time spans: time of day, day of the week and dayof the month. The objective is to evaluate the ve methods in thethree time spans and decide which method is the most suitable foreach of them. Methods. This study includes three experiments testing all ve methodson the three time spans. The experiments focus on comparing theobserved data against the data of burglaries with a known specictime of the crime. In order to test the performance of each method aChi-squared goodness-of-t test was used, as well as a visual comparisonof the produced plots. Results. The results showed that the Aoristic-method was the mostsuitable method to use when analysing temporal data of residentialburglars, if looking at the time of day, day of the week and day ofthe month. Using the methods we also generated plots of the threetemporal distributions, with an R script. Conclusions. We concluded that using the Aoristic-method is themost suitable method to use to generate plots from the temporal data.We also concluded that using this script with the Aoristic-method togenerate plots, would make it possible for the police to resource allocationaccording to when burglaries actually take place.
author Svenhag, Olle
author_facet Svenhag, Olle
author_sort Svenhag, Olle
title Utvärdering av temporala analysmetoder inom brottskategorin bostadsinbrott
title_short Utvärdering av temporala analysmetoder inom brottskategorin bostadsinbrott
title_full Utvärdering av temporala analysmetoder inom brottskategorin bostadsinbrott
title_fullStr Utvärdering av temporala analysmetoder inom brottskategorin bostadsinbrott
title_full_unstemmed Utvärdering av temporala analysmetoder inom brottskategorin bostadsinbrott
title_sort utvärdering av temporala analysmetoder inom brottskategorin bostadsinbrott
publisher Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik
publishDate 2015
url http://urn.kb.se/resolve?urn=urn:nbn:se:bth-10476
work_keys_str_mv AT svenhagolle utvarderingavtemporalaanalysmetoderinombrottskategorinbostadsinbrott
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