Classification for predicting offender affiliation with murder victims

Yang, Rui; Ólafsson, Sigurđur

doi:10.1016/j.eswa.2011.03.051

Cited by 8 publications

(9 citation statements)

References 29 publications

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“…Finally, it has been shown that in the case of perpetrators who previously knew their victims, there tends to be a greater number and seriousness of injuries [41], with the homicides tending to take place indoors and most often using bladed weapons or blunt objects [32,42]. In addition, they tend to be triggered by an argument [33,43]; similarly, the victims are usually male and between the ages of 15 and 24 [44]. Also, homicides committed in the family setting are associated with victims who are usually minors and elderly individuals, and suffocation and poisoning predominate as the homicide methods used [37,39,40,44].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, they tend to be triggered by an argument [33,43]; similarly, the victims are usually male and between the ages of 15 and 24 [44]. Also, homicides committed in the family setting are associated with victims who are usually minors and elderly individuals, and suffocation and poisoning predominate as the homicide methods used [37,39,40,44]. In homicides taking place between couples, the victims tend to be females, aged between 19 and 50, means are commonly used to control the victim, and bladed weapons and blunt objects are most often used [39,44].…”

Section: Introductionmentioning

confidence: 99%

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Homicide Profiles Based on Crime Scene and Victim Characteristics

Pecino-Latorre

Fuentes

Patró-Hernández

2019

IJERPH

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One of the current trends in homicide research includes developing works based on scientific study and empirical evidence, which offer conclusions that can be used in an operational manner during police investigations. The objective of this study was to identify homicide characteristics from behaviors carried out on the crime scene and victim characteristics associated with those of the perpetrators of these crimes in Spain. The sample consisted of 448 homicide cases from the database of the Homicide Revision Project led by the Office of Coordination and Studies of the Secretary of State and Security. After creating six classification tree models, it was found that the modus operandi of the aggressor and the victim characteristics may permit hypothesizing about the demographic characteristics of the perpetrator (gender, age, and country of origin), his/her criminal record, and the type of relationship with the victim. Furthermore, the importance of the study of victimology during a criminal investigation is highlighted, as it may indirectly offer information about the potential perpetrator. The findings of this study suggest that criminal profiling contributes notably to the decision-making process to establish more rigorous suspect prioritization, improve the management of human resources and materials, and increase the efficiency of criminal investigations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Homicide Profiles Based on Crime Scene and Victim Characteristics

Pecino-Latorre

Fuentes

Patró-Hernández

2019

IJERPH

View full text Add to dashboard Cite

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“…Research shows that the application of criminal case, victim and suspect data to data mining can help to find hidden patterns and provide decision support for law enforcement [1]. According to the historical data, Li et al [2] trains the SVM-based feature prediction model, and calculates the feature similarity with the candidate suspect database, so as to predict the suspect.…”

Section: Introductionmentioning

confidence: 99%

Application of an Ensemble Learning based Classifier in Crime Prediction

2019

Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering

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As an outstanding issue for police, crime prediction has been paid widely attention by researchers. Based on Ensemble Learning method, this paper applies random forest to classifier and introduces a crime prediction method to deeply explore the characteristics of criminal suspects to achieve the purpose of crime prevention. According to calculating attribute importance, the method keeps the important attributes in the algorithm. The reduced attribute set is used to train the random forest model to obtain the crime prediction classifier. The crime data was applied to the proposed classifier which is evaluated by the precision and recall. The experimental results show that the presented classifier is effective.

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“…A DT has been defined as 'a way to represent rules underlying data with hierarchical, sequential structures that recursively partition the data' (Murthy, 1998, p. 345). DT is a technique that learns to recognise patterns in data and has performed well in various areas of application (Quinlan, 1993;Rokach, 2007;Wu & Kumar, 2009), including criminal and forensic investigations (Abbasi & Chen, 2005;Bennell, Mugford, Ellingwood, & Woodhams, 2014;Berk & Bleich, 2013;Gutierrez & Leroy, 2008;Ngai, Hu, Wong, Chen, & Sun, 2011;Yang & Olafsson, 2011). Furthermore, DTs are used as pedagogical support tools to produce easy-to-interpret models generally (Anaya, Luque, & García-Saiz, 2013;Breiman, 2001b;Jormanainen & Sutinen, 2012).…”

Section: Introductionmentioning

confidence: 99%

Characterising the Personality of the Public Safety Offender and Non‐offender using Decision Trees: The Case of Colombia

Masías

Valle

Amar

et al. 2016

Journal Invest Psychology

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The aim of this paper was to create a decision tree (DT) to identify personality profiles of offenders against public safety. A technique meeting this requirement was proposed that uses the C4.5 algorithm to derive decision rules for personality profiling of public safety offenders. The Mini-Mult test was used to measure the personality profiles of 238 individuals. With the test results as our database, a C4.5 DT was applied to construct rules that classify each profile into one of two groups, those without and those with records of offences against public safety. The model correctly classified 80% of the personality profiles and delivered a set of decision rules for distinguishing the profiles by group, and the principal personality profiles were interpreted. We conclude that DTs are a promising technique for analysing personality profiles by their offender or non-offender status. Finally, we believe that the development of a classifying model using DT may have practical applications in the Colombian prison syste

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Classification for predicting offender affiliation with murder victims

Cited by 8 publications

References 29 publications

Homicide Profiles Based on Crime Scene and Victim Characteristics

Homicide Profiles Based on Crime Scene and Victim Characteristics

Application of an Ensemble Learning based Classifier in Crime Prediction

Characterising the Personality of the Public Safety Offender and Non‐offender using Decision Trees: The Case of Colombia

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