Modeling and prediction of road traffic accidents in the district of Setúbal

Publicações

A Graph Database Representation of Portuguese Criminal-Related Documents

Publication . Carnaz, Gonçalo; Nogueira, Vitor Beires; Antunes, Mário

Organizations have been challenged by the need to process an increasing amount of data, both structured and unstructured, retrieved from heterogeneous sources. Criminal investigation police are among these organizations, as they have to manually process a vast number of criminal reports, news articles related to crimes, occurrence and evidence reports, and other unstructured documents. Automatic extraction and representation of data and knowledge in such documents is an essential task to reduce the manual analysis burden and to automate the discovering of names and entities relationships that may exist in a case. This paper presents SEMCrime, a framework used to extract and classify named-entities and relations in Portuguese criminal reports and documents, and represent the data retrieved into a graph database. A 5WH1 (Who, What, Why, Where, When, and How) information extraction method was applied, and a graph database representation was used to store and visualize the relations extracted from the documents. Promising results were obtained with a prototype developed to evaluate the framework, namely a name-entity recognition with an F-Measure of 0.73, and a 5W1H information extraction performance with an F-Measure of 0.65.

2021-06-04Artigo científico

Acesso aberto

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Palavras-chave

Statistical modelling,Big data,Traffic road accidents,Geographic information system , Exact sciences

Entidade financiadora

Fundação para a Ciência e a Tecnologia, I.P.

Programa de financiamento

Concurso de Projetos de Investigação Científica e Desenvolvimento Tecnológico em Ciência dos dados e inteligência artificial na Administração Pública - 2018

Número da atribuição

DSAIPA/DS/0090/2018