Knowledge Representation of Crime-Related Events: a Preliminary Approach

Authors Gonçalo Carnaz , Vitor Beires Nogueira , Mário Antunes

Thumbnail PDF


  • Filesize: 0.6 MB
  • 8 pages

Document Identifiers

Author Details

Gonçalo Carnaz
  • Department of Informatics, University of Évora, Portugal
Vitor Beires Nogueira
  • Department of Informatics, University of Évora, Portugal
Mário Antunes
  • School of Technology and Management, Polytechnic Institute of Leiria, Portugal
  • INESC-TEC, CRACS, University of Porto, Porto, Portugal

Cite AsGet BibTex

Gonçalo Carnaz, Vitor Beires Nogueira, and Mário Antunes. Knowledge Representation of Crime-Related Events: a Preliminary Approach. In 8th Symposium on Languages, Applications and Technologies (SLATE 2019). Open Access Series in Informatics (OASIcs), Volume 74, pp. 13:1-13:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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).

Subject Classification

ACM Subject Classification
  • Information systems → Information retrieval
  • Information systems → Ontologies
  • SEM Ontology
  • Relation Extraction
  • Crime-Related Events
  • SVO Algorithm
  • Ontology Population


  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    PDF Downloads


  1. JAPJ Breukers and RJ Hoekstra. Epistemology and ontology in core ontologies: FOLaw and LRI-Core, two. Citeseer, 2004. Google Scholar
  2. José Guilherme Mírian Bruckschen, Re-nata Vieira Souza, and Sandro Rigo. Desafios na avaliação conjunta do reconhecimento de entidades mencionadas: O Segundo HAREM. Desafios na avaliação conjunta do reconhecimento de entidades mencionadas: O Segundo HAREM, page 436, 2008. Google Scholar
  3. Nuno Cardoso. Rembrandt-reconhecimento de entidades mencionadas baseado em relaçoes e análise detalhada do texto. quot; Encontro do Segundo HAREM (Universidade de Aveiro Portugal 7 de Setembro de 2008), 2008. Google Scholar
  4. Pompeu Casanovas, Núria Casellas, Christoph Tempich, Denny Vrandečić, and Richard Benjamins. OPJK and DILIGENT: ontology modeling in a distributed environment. Artificial Intelligence and Law, 15(2):171-186, 2007. Google Scholar
  5. Sandra Collovini, Gabriel Machado, and Renata Vieira. A Sequence Model Approach to Relation Extraction in Portuguese. In LREC, 2016. Google Scholar
  6. John Davies. Lightweight ontologies. In Theory and Applications of Ontology: Computer Applications, pages 197-229. Springer, 2010. Google Scholar
  7. Cleyton Mário de Oliveira Rodrigues, Frederico Luiz Goncalves De Freitas, and Ryan Ribeiro De Azevedo. An ontology for property crime based on events from ufo-b foundational ontology. In 2016 5th Brazilian Conference on Intelligent Systems (BRACIS), pages 331-336. IEEE, 2016. Google Scholar
  8. Enrico Francesconi, Pier-Luigi Spinosa, and Daniela Tiscornia. A Linguistic-ontological Support for Multilingual Legislative Drafting: the DALOS Project. In LOAIT, pages 103-111, 2007. Google Scholar
  9. Marcos Garcia and Pablo Gamallo. Evaluating various linguistic features on semantic relation extraction. In Proceedings of the International Conference Recent Advances in Natural Language Processing 2011, pages 721-726, 2011. Google Scholar
  10. Marko Marković, Stevan Gostojić, and Zora Konjović. Structural and semantic markup of complaints: Case study of Serbian Judiciary. In 2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (SISY), pages 15-20. IEEE, 2014. Google Scholar
  11. Marguerite McDaniel, Emma Sloan, William Nick, James Mayes, and Albert Esterline. Ontologies for situation-based crime scene identities. In SoutheastCon 2017, pages 1-8. IEEE, 2017. Google Scholar
  12. Murad Mehmet and Duminda Wijesekera. Ontological Constructs to Create Money Laundering Schemes. In STIDS, pages 21-29. Citeseer, 2010. Google Scholar
  13. Imen Bouaziz Mezghanni and Faiez Gargouri. CrimAr: A Criminal Arabic Ontology for a Benchmark Based Evaluation. Procedia Computer Science, 112:653-662, 2017. Google Scholar
  14. Cristina Mota and Diana Santos. Desafios na avaliação conjunta do reconhecimento de entidades mencionadas: O Segundo HAREM. In Desafios na avaliação conjunta do reconhecimento de entidades mencionadas: O Segundo HAREM, chapter : Geo-ontologias e padrões para reconhecimento de locais e de suas relações em textos: o SEI-Geo no Segundo HAREM, page 436. Desafios na avaliação conjunta do reconhecimento de entidades mencionadas: O Segundo HAREM, 2008. URL:
  15. Quratulain Rajput, Nida Sadaf Khan, Asma Larik, and Sajjad Haider. Ontology based expert-system for suspicious transactions detection. Computer and Information Science, 7(1):103, 2014. Google Scholar
  16. Ricardo Manuel da Conceição Rodrigues. RAPPORT: A Fact-Based Question Answering System for Portuguese. PhD thesis, Universidade de Coimbra, 2017. Google Scholar
  17. Erick Nilsen Pereira Souza and Daniela Barreiro Claro. Extração de relações utilizando features diferenciadas para português. Linguamática, 6(2):57-65, 2014. Google Scholar
  18. Sylvie Szulman Sylvie Despres. Construction of a legal ontology from a european community legislative text. In Legal Knowledge and Information Systems: JURIX 2004, the Seventeenth Annual Conference, volume 120, page 79. IOS Press, 2004. Google Scholar
  19. Daniela Tiscornia. The LOIS project: Lexical ontologies for legal information sharing. In Proceedings of the V Legislative XML Workshop, pages 189-204. Citeseer, 2006. Google Scholar
  20. Saskia Van De Ven, Rinke Hoekstra, Joost Breuker, Lars Wortel, Abdallah El Ali, et al. Judging Amy: Automated Legal Assessment using OWL 2. In OWLED, volume 432, 2008. Google Scholar
Questions / Remarks / Feedback

Feedback for Dagstuhl Publishing

Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail