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

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

doi:10.1007/978-3-030-46140-9_4

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

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

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión 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 original	Inglés
Título de la publicación alojada	Information management and big data
Subtítulo de la publicación alojada	6th International Conference, SIMBig 2019, Proceedings
Editores	Juan Antonio Lossio-Ventura, Nelly Condori-Fernandez, Jorge Carlos Valverde-Rebaza
Lugar de publicación	Cham
Páginas	35-45
Número de páginas	11
ISBN (versión digital)	978-3-030-46140-9
DOI	https://doi.org/10.1007/978-3-030-46140-9_4
Estado	Publicada - 23 abr. 2020
Evento	Communications in Computer and Information Science - Duración: 1 ene. 2020 → …

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	1070 CCIS
ISSN (versión impresa)	1865-0929
ISSN (versión digital)	1865-0937

Conferencia

Conferencia	Communications in Computer and Information Science
Período	1/01/20 → …

Nota bibliográfica

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Palabras clave

Crime
Event detection
Tensor decomposition

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Acceder al documento

10.1007/978-3-030-46140-9_4

Otros archivos y enlaces

Citar esto

Alatrista-Salas, H., Lavado, P., Morzan, J., Nuñez-del-Prado, M., & Yamada, G. (2020). Detecting anomalies in time-varying media crime news using tensor decomposition. En J. A. Lossio-Ventura, N. Condori-Fernandez, & J. C. Valverde-Rebaza (Eds.), Information management and big data: 6th International Conference, SIMBig 2019, Proceedings (pp. 35-45). (Communications in Computer and Information Science; Vol. 1070 CCIS).. https://doi.org/10.1007/978-3-030-46140-9_4

Alatrista-Salas, Hugo ; Lavado, Pablo ; Morzan, Juandiego et al. / Detecting anomalies in time-varying media crime news using tensor decomposition. Information management and big data: 6th International Conference, SIMBig 2019, Proceedings. editor / Juan Antonio Lossio-Ventura ; Nelly Condori-Fernandez ; Jorge Carlos Valverde-Rebaza. Cham, 2020. pp. 35-45 (Communications in Computer and Information Science).

@inproceedings{2cfc802bb5d04bdc8db95f2c9cd94cc1,

title = "Detecting anomalies in time-varying media crime news using tensor decomposition",

abstract = "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.",

keywords = "Crime, Event detection, Tensor decomposition, Crime, Event detection, Tensor decomposition",

author = "Hugo Alatrista-Salas and Pablo Lavado and Juandiego Morzan and Miguel Nu{\~n}ez-del-Prado and Gustavo Yamada",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; Communications in Computer and Information Science ; Conference date: 01-01-2020",

year = "2020",

month = apr,

day = "23",

doi = "10.1007/978-3-030-46140-9_4",

language = "English",

isbn = "978-3-030-46139-3",

series = "Communications in Computer and Information Science",

pages = "35--45",

editor = "Lossio-Ventura, {Juan Antonio} and Nelly Condori-Fernandez and Valverde-Rebaza, {Jorge Carlos}",

booktitle = "Information management and big data",

}

Alatrista-Salas, H, Lavado, P, Morzan, J, Nuñez-del-Prado, M & Yamada, G 2020, Detecting anomalies in time-varying media crime news using tensor decomposition. En JA Lossio-Ventura, N Condori-Fernandez & JC Valverde-Rebaza (eds.), Information management and big data: 6th International Conference, SIMBig 2019, Proceedings. Communications in Computer and Information Science, vol. 1070 CCIS, Cham, pp. 35-45, Communications in Computer and Information Science, 1/01/20. https://doi.org/10.1007/978-3-030-46140-9_4

Detecting anomalies in time-varying media crime news using tensor decomposition. / Alatrista-Salas, Hugo; Lavado, Pablo; Morzan, Juandiego et al.
Information management and big data: 6th International Conference, SIMBig 2019, Proceedings. ed. / Juan Antonio Lossio-Ventura; Nelly Condori-Fernandez; Jorge Carlos Valverde-Rebaza. Cham, 2020. p. 35-45 (Communications in Computer and Information Science; Vol. 1070 CCIS).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Detecting anomalies in time-varying media crime news using tensor decomposition

AU - Alatrista-Salas, Hugo

AU - Lavado, Pablo

AU - Morzan, Juandiego

AU - Nuñez-del-Prado, Miguel

AU - Yamada, Gustavo

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020/4/23

Y1 - 2020/4/23

N2 - 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.

AB - 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.

KW - Crime

KW - Event detection

KW - Tensor decomposition

KW - Crime

KW - Event detection

KW - Tensor decomposition

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85084795913&origin=inward

UR - http://www.scopus.com/inward/record.url?scp=85084795913&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/fefe664b-e9fb-33c2-afd9-8b8a2b3a9057/

U2 - 10.1007/978-3-030-46140-9_4

DO - 10.1007/978-3-030-46140-9_4

M3 - Conference contribution

SN - 978-3-030-46139-3

T3 - Communications in Computer and Information Science

SP - 35

EP - 45

BT - Information management and big data

A2 - Lossio-Ventura, Juan Antonio

A2 - Condori-Fernandez, Nelly

A2 - Valverde-Rebaza, Jorge Carlos

CY - Cham

T2 - Communications in Computer and Information Science

Y2 - 1 January 2020

ER -

Alatrista-Salas H, Lavado P, Morzan J, Nuñez-del-Prado M, Yamada G. Detecting anomalies in time-varying media crime news using tensor decomposition. En Lossio-Ventura JA, Condori-Fernandez N, Valverde-Rebaza JC, editores, Information management and big data: 6th International Conference, SIMBig 2019, Proceedings. Cham. 2020. p. 35-45. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-46140-9_4

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

Resumen

Serie de la publicación

Conferencia

Nota bibliográfica

Palabras clave

ODS de las Naciones Unidas

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto