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Mexican International Conference on Artificial Intelligence

MICAI 2017: Advances in Computational Intelligence pp 120–132Cite as

Criminal Events Detection in News Stories Using Intuitive Classification

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10633))

Abstract

This paper proposes a model for the identification of criminal events through the analysis of journalistic news implementing classification mechanism. The classification process is composed of three sub-process: Information Extraction, Classification process and a Selection process of the classes with the best scores obtained after the classification. To obtain the harmonic mean between recall and precision (F-Score) of this classification model, a criminological corpus called CAD was used to simulate different scenarios. CAD is a corpus in spanish composed of news reporting crimes about homicide, assaults, kidnapping, sexual abuse, and extortion, called High Impact Crimes according to [1].

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Notes

  1. 1.

    To get a copy of corpus CAD send a mail to luismoreno@cenidet.edu.mx/ncastro@cenidet.edu.mx.

  2. 2.

    http://www.wikicrimes.org.

  3. 3.

    http://www.launion.com.mx.

  4. 4.

    http://www.diariodemorelos.com.

  5. 5.

    http://www.jornadamorelos.com.

  6. 6.

    Master Students.

  7. 7.

    https://www.diariodemorelos.com/noticias.

  8. 8.

    http://www.cs.waikato.ac.nz/ml/weka.

  9. 9.

    http://nlp.lsi.upc.edu/freeling/node/1.

References

  1. Observatorio Nacional Ciudadano Seguridad, Justicia y Legalidad: Reporte sobre delitos de alto impacto Junio 2016. Reporte Año 3, No. 5, México (2016)

    Google Scholar 

  2. Kumar, A.S., Gopal, R.K.: Data mining based crime investigation systems: taxonomy and relevance. In: 2015 Global Conference on Communication Technologies (GCCT), pp. 850–853. IEEE (2015)

    Google Scholar 

  3. Ku, C.H., Iriberri, A., Leroy, G.: Crime information extraction from police and witness narrative reports. In: International Conference on Technologies for Homeland Security, pp. 193–198. IEEE (2008)

    Google Scholar 

  4. Nath, S.V.: Crime data mining. In: Elleithy, K. (ed.) Advances and Innovations in Systems, Computing Sciences and Software Engineering, pp. 405–409. Springer, Dordrecht (2007). https://doi.org/10.1007/978-1-4020-6264-3_70

    Chapter  Google Scholar 

  5. Ku, C.H., Leroy, G.: A decision support system: automated crime report analysis and classification for e-government. Gov. Inf. Q. 31, 534–544 (2014)

    Article  Google Scholar 

  6. Dahbur, K., Muscarello, T.: Classification system for serial criminal patterns. Artif. Intell. Law 11, 251–269 (2003)

    Article  Google Scholar 

  7. Chau, M., Xu, J.J., Chen, H.: Extracting meaningful entities from police narrative reports. In: Proceedings of the 2002 Annual National Conference on Digital Government Research, Digital Government Society of North America, pp. 1–5 (2002)

    Google Scholar 

  8. Lee, S., Kim, H.J.: News keyword extraction for topic tracking. In: Fourth International Conference on Networked Computing and Advanced Information Management, NCM 2008, vol. 2, pp. 554–559. IEEE (2008)

    Google Scholar 

  9. Pinheiro, V., Furtado, V., Pequeno, T., Nogueira, D.: Natural language processing based on semantic inferentialism for extracting crime information from text. In: International Conference on Intelligence and Security Informatics ISI, pp. 19–24. IEEE (2010)

    Google Scholar 

  10. Estivill-Castro, V., Lee, I.: Data mining techniques for autonomous exploration of large volumes of geo-referenced crime data. In: Proceedings of the 6th International Conference on Geocomputation, pp. 24–26 (2001)

    Google Scholar 

  11. Chen, H., Chung, W., Xu, J.J., Wang, G., Qin, Y., Chau, M.: Crime data mining: a general framework and some examples. Computer 37, 50–56 (2004)

    Article  Google Scholar 

  12. Moreno Jiménez, L.G., et al.: Creación y clasificación de un corpus criminológico en español usando características lingüísticas superficiales. Research in Computing Science (2016, accepted)

    Google Scholar 

  13. Associated Press: 2016 AP Stylebook. Spiral-Bound (2016)

    Google Scholar 

  14. Torres-Moreno, J.M.: Automatic Text Summarization. Wiley, Hoboken (2014)

    Book  Google Scholar 

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Acknowledgments

This work was supported by Mexican Government (Tecnológico Nacional de México/CENIDET, Red Temática en Tecnologías del Lenguaje-Conacyt, Conacyt scholarship 661101) and French Government (Université d’ Avignon et des Pays de Vaucluse/Laboratoire Informatique d’ Avignon).

Author information

Authors and Affiliations

  1. Centro Nacional de Investigación y Desarrollo Tecnológico, Tecnológico Nacional de México, Cuernavaca, Mexico

    Luis-Gil Moreno-Jiménez, Noé Alejandro Castro-Sánchez & Alondra Nava-Zea

  2. LIA/Université d’Avignon et des Pays de Vaucluse, Avignon, France

    Juan-Manuel Torres-Moreno

  3. École Polytechnique de Montréal, Montreal, Canada

    Juan-Manuel Torres-Moreno

  4. Universidad Nacional Autónoma de México, Mexico City, Mexico

    Gerardo Sierra

Authors
  1. Luis-Gil Moreno-Jiménez
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  2. Juan-Manuel Torres-Moreno
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  3. Noé Alejandro Castro-Sánchez
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  4. Alondra Nava-Zea
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  5. Gerardo Sierra
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Corresponding author

Correspondence to Luis-Gil Moreno-Jiménez .

Editor information

Editors and Affiliations

  1. Universidad Autónoma del Estado de Hidalgo, Pachuca, Mexico

    Félix Castro

  2. INFOTEC Aguascalientes, Aguascalientes, Mexico

    Sabino Miranda-Jiménez

  3. Tecnológico de Monterrey, Atizapán de Zaragoza, Mexico

    Miguel González-Mendoza

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Moreno-Jiménez, LG., Torres-Moreno, JM., Castro-Sánchez, N.A., Nava-Zea, A., Sierra, G. (2018). Criminal Events Detection in News Stories Using Intuitive Classification. In: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (eds) Advances in Computational Intelligence. MICAI 2017. Lecture Notes in Computer Science(), vol 10633. Springer, Cham. https://doi.org/10.1007/978-3-030-02840-4_10

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  • DOI: https://doi.org/10.1007/978-3-030-02840-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02839-8

  • Online ISBN: 978-3-030-02840-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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