Detecting anomalies in time-varying media crime news using tensor decomposition

Hugo Alatrista-Salas, Pablo Lavado, Juandiego Morzan, Miguel Nuñez-del-Prado, Gustavo Yamada

Resultado de la investigación: Capítulo del libro/informe/acta de congresoCapítulo de librorevisión exhaustiva

Resumen

Nowadays, the mass media surround us in many forms. Newspapers, radio and TV reports about many topics, including the crime committed in a region. Indirectly, the media provide statistics about crime incidents, and policymakers could focus their attention on the unusual number of crime news (c.f., regular events) for evaluating and proposing new public policies. In the present work, the Tensor decomposition is used to detect an unusual amount of crime news. To achieve this goal, two rejection criterion techniques were compared. Also, several image binarization techniques were used to validate our proposal. Our result can be used to detect an unusual amount of crime news as a proxy of unusual crime activity.
Idioma originalInglés
Título de la publicación alojadaInformation management and big data
Subtítulo de la publicación alojada6th International Conference, SIMBig 2019, Proceedings
EditoresJuan Antonio Lossio-Ventura, Nelly Condori-Fernandez, Jorge Carlos Valverde-Rebaza
Lugar de publicaciónCham
EditorialSpringer
Páginas35-45
Número de páginas11
ISBN (versión digital)978-3-030-46140-9
ISBN (versión impresa)978-3-030-46139-3
DOI
EstadoPublicada - 23 abr. 2020
EventoCommunications in Computer and Information Science -
Duración: 1 ene. 2020 → …

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen1070 CCIS
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

ConferenciaCommunications in Computer and Information Science
Período1/01/20 → …

Nota bibliográfica

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Palabras clave

  • Crime
  • Event detection
  • Tensor decomposition

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