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.
|Title of host publication||Information management and big data|
|Subtitle of host publication||6th International Conference, SIMBig 2019, Proceedings|
|Editors||Juan Antonio Lossio-Ventura, Nelly Condori-Fernandez, Jorge Carlos Valverde-Rebaza|
|Place of Publication||Cham|
|Number of pages||11|
|State||Published - 23 Apr 2020|
|Event||Communications in Computer and Information Science - |
Duration: 1 Jan 2020 → …
|Name||Communications in Computer and Information Science|
|Conference||Communications in Computer and Information Science|
|Period||1/01/20 → …|
Bibliographical notePublisher Copyright:
© Springer Nature Switzerland AG 2020.
- Event detection
- Tensor decomposition