Predictive model for criminality in Lisbon

V. Lobo; Fernando Bação; Paulo João

Predictive model for criminality in Lisbon

NOVA Information Management School (NOVA IMS)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper uses a combination of hot spotting analysis with a geographical information system based on SAS Enterprise Miner model, it also detail a forecasting framework for short-term, tactical deployment of police resources in which the objective is the identification of areas where the levels of crime are high enough to enable accurate predictive models to be produced.

Original language	English
Title of host publication	JOCLAD’2010 - XVII Jornadas de Classificação e Análise de Dados
Pages	1-13
Number of pages	13
Publication status	Published - 2010

Keywords

Crime Analyze, Data Mining, Geographic Information System, Neural Network, Hot-Spot, Predictive Model

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "Predictive model for criminality in Lisbon",

abstract = "This paper uses a combination of hot spotting analysis with a geographical information system based on SAS Enterprise Miner model, it also detail a forecasting framework for short-term, tactical deployment of police resources in which the objective is the identification of areas where the levels of crime are high enough to enable accurate predictive models to be produced.",

keywords = "Crime Analyze, Data Mining, Geographic Information System, Neural Network, Hot-Spot, Predictive Model",

author = "V. Lobo and Fernando Ba{\c c}{\~a}o and Paulo Jo{\~a}o",

year = "2010",

language = "English",

pages = "1--13",

booktitle = "JOCLAD{\textquoteright}2010 - XVII Jornadas de Classifica{\c c}{\~a}o e An{\'a}lise de Dados",

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TY - GEN

T1 - Predictive model for criminality in Lisbon

AU - Lobo, V.

AU - Bação, Fernando

AU - João, Paulo

PY - 2010

Y1 - 2010

N2 - This paper uses a combination of hot spotting analysis with a geographical information system based on SAS Enterprise Miner model, it also detail a forecasting framework for short-term, tactical deployment of police resources in which the objective is the identification of areas where the levels of crime are high enough to enable accurate predictive models to be produced.

AB - This paper uses a combination of hot spotting analysis with a geographical information system based on SAS Enterprise Miner model, it also detail a forecasting framework for short-term, tactical deployment of police resources in which the objective is the identification of areas where the levels of crime are high enough to enable accurate predictive models to be produced.

KW - Crime Analyze, Data Mining, Geographic Information System, Neural Network, Hot-Spot, Predictive Model

M3 - Conference contribution

SP - 1

EP - 13

BT - JOCLAD’2010 - XVII Jornadas de Classificação e Análise de Dados

ER -

Predictive model for criminality in Lisbon

Abstract

Keywords

UN SDGs

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Cite this