License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.SLATE.2019.13
URN: urn:nbn:de:0030-drops-108809
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2019/10880/
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Carnaz, Gonçalo ; Nogueira, Vitor Beires ; Antunes, Mário

Knowledge Representation of Crime-Related Events: a Preliminary Approach

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OASIcs-SLATE-2019-13.pdf (0.6 MB)

Abstract

The crime is spread in every daily newspaper, and particularly on criminal investigation reports produced by several Police departments, creating an amount of data to be processed by Humans. Other research studies related to relation extraction (a branch of information retrieval) in Portuguese arisen along the years, but with few extracted relations and several computer methods approaches, that could be improved by recent features, to achieve better performance results.
This paper aims to present the ongoing work related to SEM (Simple Event Model) ontology population with instances retrieved from crime-related documents, supported by an SVO (Subject, Verb, Object) algorithm using hand-crafted rules to extract events, achieving a performance measure of 0.86 (F-Measure).

BibTeX - Entry

@InProceedings{carnaz_et_al:OASIcs:2019:10880,
  author =	{Gon{\c{c}}alo Carnaz and Vitor Beires Nogueira and M{\'a}rio Antunes},
  title =	{{Knowledge Representation of Crime-Related Events: a Preliminary Approach}},
  booktitle =	{8th Symposium on Languages, Applications and Technologies (SLATE 2019)},
  pages =	{13:1--13:8},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-114-6},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{74},
  editor =	{Ricardo Rodrigues and Jan Janousek and Lu{\'\i}s Ferreira and Lu{\'\i}sa Coheur and Fernando Batista and Hugo Gon{\c{c}}alo Oliveira},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2019/10880},
  URN =		{urn:nbn:de:0030-drops-108809},
  doi =		{10.4230/OASIcs.SLATE.2019.13},
  annote =	{Keywords: SEM Ontology, Relation Extraction, Crime-Related Events, SVO Algorithm, Ontology Population}
}

Keywords: SEM Ontology, Relation Extraction, Crime-Related Events, SVO Algorithm, Ontology Population
Collection: 8th Symposium on Languages, Applications and Technologies (SLATE 2019)
Issue Date: 2019
Date of publication: 24.07.2019

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