Cargando…
Social Network Analysis in Predictive Policing Concepts, Models and Methods /
This book focuses on applications of social network analysis in predictive policing. Data science is used to identify potential criminal activity by analyzing the relationships between offenders to fully understand criminal collaboration patterns. Co-offending networks-networks of offenders who have...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
|
| Edición: | 1st ed. 2016. |
| Colección: | Lecture Notes in Social Networks,
|
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-41492-8 | ||
| 003 | DE-He213 | ||
| 005 | 20220115215429.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 161011s2016 sz | s |||| 0|eng d | ||
| 020 | |a 9783319414928 |9 978-3-319-41492-8 | ||
| 024 | 7 | |a 10.1007/978-3-319-41492-8 |2 doi | |
| 050 | 4 | |a QA76.9.D343 | |
| 072 | 7 | |a UNF |2 bicssc | |
| 072 | 7 | |a UYQE |2 bicssc | |
| 072 | 7 | |a COM021030 |2 bisacsh | |
| 072 | 7 | |a UNF |2 thema | |
| 072 | 7 | |a UYQE |2 thema | |
| 082 | 0 | 4 | |a 006.312 |2 23 |
| 100 | 1 | |a Tayebi, Mohammad A. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Social Network Analysis in Predictive Policing |h [electronic resource] : |b Concepts, Models and Methods / |c by Mohammad A. Tayebi, Uwe Glässer. |
| 250 | |a 1st ed. 2016. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2016. | |
| 300 | |a XI, 133 p. 43 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Lecture Notes in Social Networks, |x 2190-5436 | |
| 505 | 0 | |a Introduction -- Social Network Analysis in Predictive Policing -- Structure of Co-offending Networks -- Organized Crime Group Detection -- Suspect Investigation -- Co-offence Prediction -- Personalized Crime Location Prediction -- Concluding remarks -- References. | |
| 520 | |a This book focuses on applications of social network analysis in predictive policing. Data science is used to identify potential criminal activity by analyzing the relationships between offenders to fully understand criminal collaboration patterns. Co-offending networks-networks of offenders who have committed crimes together-have long been recognized by law enforcement and intelligence agencies as a major factor in the design of crime prevention and intervention strategies. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature. This book extensively and systematically studies co-offending network analysis as effective tool for predictive policing. The formal representation of criminological concepts presented here allow computer scientists to think about algorithmic and computational solutions to problems long discussed in the criminology literature. For each of the studied problems, we start with well-founded concepts and theories in criminology, then propose a computational method and finally provide a thorough experimental evaluation, along with a discussion of the results. In this way, the reader will be able to study the complete process of solving real-world multidisciplinary problems. | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Criminology. | |
| 650 | 0 | |a Graph theory. | |
| 650 | 0 | |a Data protection. | |
| 650 | 1 | 4 | |a Data Mining and Knowledge Discovery. |
| 650 | 2 | 4 | |a Crime Control and Security. |
| 650 | 2 | 4 | |a Graph Theory. |
| 650 | 2 | 4 | |a Data and Information Security. |
| 700 | 1 | |a Glässer, Uwe. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319414911 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319414935 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319823683 |
| 830 | 0 | |a Lecture Notes in Social Networks, |x 2190-5436 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-319-41492-8 |z Texto Completo |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||