Extraction of Rules of Association of Criminal Data in the Municipality of Goiânia
Abstract
The present work aims to extract associations in data of criminal oc-currences in the city of Goiânia, identifying the neighborhoods where there is a greater concentration of crimes, considering the spatial and temporal distribution, as well as the socioeconomic profile of the place of occurrence. The developed process uses all phases of knowledge discovery-KDD (Knowledge Discovery in Databases), including the selection of attributes, cleaning, standardization, pre-processing and data transformation. The data set used in this study refers to the record of criminal occurrences provided by the Information Analysis Management of the Public Security Secretariat of the State of Goiás. The result obtained through the use of association rules gathers important information about criminal occurrences, such as the identification of the most frequent crimes in a specific place, in a time period, with a specific victim profile. The results are relevant to help decision making and also to inform and alert the population about the places with the most criminal occurrences at certain times in the municipality of Goiânia.
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