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020 _a9783319414928
024 7 _a10.1007/978-3-319-41492-8
_2doi
040 _aES-MaUEC
050 4 _aHV7936.A8
_bT39 2016 EB
082 0 4 _a006.312
100 1 _aTayebi, Mohammad A.
_999808
_0Local
245 1 0 _aSocial Network Analysis in Predictive Policing :
_bConcepts, Models and Methods
_cby Mohammad A. Tayebi, Uwe Glässer
264 1 _aCham
_bSpringer International Publishing
_c2016
300 _a1 recurso en línea (XI, 133 p.)
_b43 ilustraciones en color
336 _aTexto (visual)
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
490 1 _aLecture Notes in Social Networks
_x2190-5428
505 0 _aIntroduction -- 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 _aThis 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 networksnetworks of offenders who have committed crimes togetherhave 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.
710 2 _aSpringerLink (Online service)
_0Local
_9106996
942 _2lcc
_cLE
988 _aEBOOK, EBSPRINGER
650 7 _aProceso de datos
_0comprobar BNE19900995159
_2embne
_9141180
650 7 _aSeguridad informática
_0comprobar BNE20010505695
_2embne
_9158200
650 7 _aData mining
_0comprobar BNE20033218554
_2embne
_9162648
700 1 _aGlässer, Uwe
_999809
_0Local
830 0 _aLecture Notes in Social Networks
_x2190-5428
_9134273
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-41492-8
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9783319414928
907 _a.b1295519x
_b10-10-17
_c21-11-16
998 _am
_a_alco
_a_vill
_b15-09-17
_cm
_dz
_ei
_feng
_ggw
_h0
945 _aHV7936.A8 T39 2016 EB
_g1
_ieBOOK
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_o-
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_z06-04-17
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