Intelligent Data Mining in Law Enforcement Analytics (Record no. 48461)
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| fixed length control field | 04980nam a22004697a 4500 |
| 001 - CONTROL NUMBER | |
| control field | sulb-eb0026369 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | BD-SySUS |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20160413122639.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 121204s2013 ne | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9789400749146 |
| -- | 978-94-007-4914-6 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-94-007-4914-6 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | H61-61.95 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | JHBC |
| Source | bicssc |
| Subject category code | SOC019000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 300.1 |
| Edition number | 23 |
| 245 10 - TITLE STATEMENT | |
| Title | Intelligent Data Mining in Law Enforcement Analytics |
| Medium | [electronic resource] : |
| Remainder of title | New Neural Networks Applied to Real Problems / |
| Statement of responsibility, etc. | edited by Massimo Buscema, William J. Tastle. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Dordrecht : |
| Name of producer, publisher, distributor, manufacturer | Springer Netherlands : |
| -- | Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2013. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XVIII, 518 p. |
| Other physical details | online resource. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS | |
| File type | text file |
| Encoding format | |
| Source | rda |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Dedication -- Preface.- Chapter 1. Introduction to Artificial Networks and Law Enforcement Analytics; William J. Tastle -- Chapter 2. Law Enforcement and Artificial Intelligence; Massimo Buscema -- Chapter 3. The General Philosophy of Artificial Adaptive Systems; Massimo Buscema -- Chapter 4. A Brief Introduction to Evolutionary Algorithms and the Genetic Doping Algorithm; M. Buscema, M. Capriotti -- Chapter 5. Artificial Adaptive Systems in Data Visualization: Pro-Active data; Massimo Buscema -- Chapter 6. The Metropolitan Police Service Central Drug Trafficking Database: Evidence of Need; Geoffrey Monaghan and Stefano Terzi -- Chapter 7. Supervised Artificial neural Networks: Back Propagation Neural Networks; Massimo Buscema -- Chapter 8. Pre-Processing Tools for Non-Linear Data Sets; Massimo Buscema, Alessandra Mancini and Marco Breda -- Chapter 9. Metaclassifiers; Massimo Buscema, Stefano Terzi -- Chapter 10. Auto Identification of a Drug Seller Utilizing a Specialized Supervised Neural Network; Massimo Buscema and Marco Intraligi -- Chapter 11. Visualization and Clustering of Self-Organizing Maps; Giulia Massini -- Chapter 12. Self-Organizing Maps: Identifying Non-Linear Relationships in Massive Drug Enforcement Databases; Guila Massini -- Chapter 13. Theory of Constraint Satisfaction Neural Networks; Massimo Buscema -- Chapter 14. Application of the Constraint Satisfaction Network; Marco Intraligi and Massimo Buscema -- Chapter 15. Auto-Contractive Maps, h Function and the Maximally regular Graph: A new methodology for data mining; Massimo Buscema -- Chapter 16. Analysis of a Complex Dataset Using the Combined MST and Auto Contractive Map; Giovanni Pieri -- Chapter 17. Auto Contractive Mapsand Minimal Spanning tree: Organization of Complex datasets on criminal behavior to aid in the deduction of network connectivity; Giula Massini and Massimo Buscema -- Chapter 18. Data Mining Using Non-linear Auto Associative Artificial Neural Networks: The Arrestee Dataset; Massimo Buscema -- Chapter 19. Artificial Adaptive System for Parallel Querying of Multiple Databases; Massimo Buscema.-. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This book provides a thorough summary of the means currently available to the investigators of Artificial Intelligence for making criminal behavior (both individual and collective) foreseeable, and for assisting their investigative capacities. The volume provides chapters on the introduction of artificial intelligence and machine learning suitable for an upper level undergraduate with exposure to mathematics and some programming skill or a graduate course. It also brings the latest research in Artificial Intelligence to life with its chapters on fascinating applications in the area of law enforcement, though much is also being accomplished in the fields of medicine and bioengineering. Individuals with a background in Artificial Intelligence will find the opening chapters to be an excellent refresher but the greatest excitement will likely be the law enforcement examples, for little has been done in that area. The editors have chosen to shine a bright light on law enforcement analytics utilizing artificial neural network technology to encourage other researchers to become involved in this very important and timely field of study. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Social sciences. |
| Topical term or geographic name as entry element | Artificial intelligence. |
| Topical term or geographic name as entry element | Neural networks (Computer science). |
| Topical term or geographic name as entry element | Social Sciences. |
| Topical term or geographic name as entry element | Methodology of the Social Sciences. |
| Topical term or geographic name as entry element | Artificial Intelligence (incl. Robotics). |
| Topical term or geographic name as entry element | Mathematical Models of Cognitive Processes and Neural Networks. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Buscema, Massimo. |
| Relator term | editor. |
| Personal name | Tastle, William J. |
| Relator term | editor. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9789400749139 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="http://dx.doi.org/10.1007/978-94-007-4914-6">http://dx.doi.org/10.1007/978-94-007-4914-6</a> |
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| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
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