Estimating and predicting the temporal information of apartment burglaries that possess imprecise time stamps: A comparative study using eight different temporal approximation methods in Vienna, Austria

Author:

Glasner PhilipORCID,Leitner MichaelORCID,Oswald Lukas

Abstract

This research compares and evaluates different approaches to approximate offense times of crimes. It contributes to and extends all previously proposed naïve and aoristic temporal approximation methods and one recent study [1] that showed that the addition of historical crimes with accurately known time stamps to temporal approximation methods can outperform all traditional approximation methods. It is paramount to work with crime data that possess precise temporal information to conduct reliable (spatiotemporal) analysis and modeling. This study contributes to and extends existing studies on temporal analysis. One novel and one relatively new temporal approximation methods are introduced that rely on weighting aoristic scores with historic offenses with exactly known offense times. It is hypothesized that these methods enhance the accuracy of the temporal approximation. In total, eight different methods are evaluated for apartment burglaries in Vienna, Austria, for yearly and seasonal differences. Results show that the one novel and one relatively new method applied in this research outperform all other existing approximation methods to estimate and predict offense times. These two methods are particularly useful for both researchers and practitioners, who often work with temporally imprecise crime data.

Funder

Austrian Science Fund

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference30 articles.

1. Evaluating Temporal Approximation Methods Using Burglary Data;L. Oswald;ISPRS International Journal of Geo-Information,2020

2. Social change and crime rate trends: A routine activity approach;L.E. Cohen;American Sociological Review,1979

3. Hot spots of predatory crime: Routine activities and the criminology of place;L.W. Sherman;Criminology,1989

4. Urban Crime Mapping and Analysis using GIS;M. Leitner;Special Issue of ISPRS International Journal of Geo-Information,2020

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Spatiotemporal Analysis of Nighttime Crimes in Vienna, Austria;ISPRS International Journal of Geo-Information;2024-07-10

2. A deep learning framework for predicting burglaries based on multiple contextual factors;Expert Systems with Applications;2022-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3