Traffic mining applied to police activities : proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017) /: proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017). ([2018])
- Record Type:
- Book
- Title:
- Traffic mining applied to police activities : proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017) /: proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017). ([2018])
- Main Title:
- Traffic mining applied to police activities : proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017)
- Further Information:
- Note: Fabio Leuzzi, Stefano Ferilli, editors.
- Editors:
- Leuzzi, Fabio
Ferilli, Stefano - Other Names:
- Italian Conference for the Traffic Police, 1st
- Contents:
- Intro; Foreword; Preface; Organization; Executive Committee; Program Committee; Organizing Committee; Sponsoring Institutions; Contents; Part I Invited Talks; Data and Analytics Framework. How Public Sector Can Profit from Its Immense Asset, Data; 1 Introduction; 2 Big Data Analytics for the Public Administration; 3 Big Data and Public Policy; 4 Data and Analytics Framework for the Public Administration; 5 Services Provided by the DAF; 6 Architectural Design Highlights; 7 Conclusions; References; Advancements in Mobility Data Analysis; 1 Big Mobility Data Sources. 2 Collective Mobility Data Analysis3 Individual Mobility Data Analysis; 4 Mobility Data-Driven Applications and Services; 5 Conclusions; References; Part II Technical Contributions; Towards a Pervasive and Predictive Traffic Police; 1 Introduction; 2 Research Fields: Background and Challenges; 2.1 Mining Traffic Data; 2.2 Hints of Vehicle Forensics and Analytics; 2.3 Mining Patrolling Data; 2.4 Mining Information Exchange Among Control Rooms; 3 An Integrated Approach to Road Understanding and Event Management; 4 Conclusions; References. A Process Mining Approach to the Identification of Normal and Suspect Traffic Behavior1 Introduction; 2 The WoMan Framework; 2.1 Input Formalism; 2.2 Output Formalism; 3 Workflow Supervision and Prediction; 4 Proposal for Application to Traffic Understanding; 4.1 Setting; 4.2 Motivation; 4.3 Example; 5 Conclusions and Future Work; References; Detecting Criminal Behaviour Patterns inIntro; Foreword; Preface; Organization; Executive Committee; Program Committee; Organizing Committee; Sponsoring Institutions; Contents; Part I Invited Talks; Data and Analytics Framework. How Public Sector Can Profit from Its Immense Asset, Data; 1 Introduction; 2 Big Data Analytics for the Public Administration; 3 Big Data and Public Policy; 4 Data and Analytics Framework for the Public Administration; 5 Services Provided by the DAF; 6 Architectural Design Highlights; 7 Conclusions; References; Advancements in Mobility Data Analysis; 1 Big Mobility Data Sources. 2 Collective Mobility Data Analysis3 Individual Mobility Data Analysis; 4 Mobility Data-Driven Applications and Services; 5 Conclusions; References; Part II Technical Contributions; Towards a Pervasive and Predictive Traffic Police; 1 Introduction; 2 Research Fields: Background and Challenges; 2.1 Mining Traffic Data; 2.2 Hints of Vehicle Forensics and Analytics; 2.3 Mining Patrolling Data; 2.4 Mining Information Exchange Among Control Rooms; 3 An Integrated Approach to Road Understanding and Event Management; 4 Conclusions; References. A Process Mining Approach to the Identification of Normal and Suspect Traffic Behavior1 Introduction; 2 The WoMan Framework; 2.1 Input Formalism; 2.2 Output Formalism; 3 Workflow Supervision and Prediction; 4 Proposal for Application to Traffic Understanding; 4.1 Setting; 4.2 Motivation; 4.3 Example; 5 Conclusions and Future Work; References; Detecting Criminal Behaviour Patterns in Spain and Italy Using Formal Concept Analysis; 1 Introduction; 2 Formal Concept Analysis; 3 Criminal Behaviour Patterns in Southern Spain; 4 Analysing Datasets of Traffic Cameras; 4.1 First Profile. 4.2 Second Profile5 Conclusions and Future Work; References; Efficient and Accurate Traffic Flow Prediction via Fast Dynamic Tensor Completion; 1 Introduction; 2 Related Works; 3 Proposed Method; 3.1 Dynamic Tensor Model for Traffic Flow; 3.2 Fast Dynamic Tensor Completion; 4 Experimental Evaluation; 4.1 Experiment Settings; 4.2 Experiment Results; 5 Conclusion; References; Reducing the Risk of Accidents with Not Insured British Vehicles in Southern Spain; 1 Introduction; 2 Methodology; 2.1 Collecting the Samples; 2.2 Weakness; 3 Results and Discussion. 3.1 A Real Case of Study in Mijas (Spain)3.2 Actual Results; 3.3 Other Results; 4 Practical Applications; 5 Conclusions and Future Work; References; Unsupervised Classification of Routes and Plates from the Trap-2017 Dataset; 1 Introduction; 2 Statistical Analysis; 3 Design of a Plates Behavior Classifier; 3.1 Overview; 3.2 The Tool; 4 Our Findings; 4.1 Tuning the Classifier; 4.2 Classifying Routes; 4.3 Classifying Plates; 5 Related Work; 5.1 Traffic Monitoring and Analysis; 5.2 Pattern Mining and Clusterization; 6 Conclusions and Future Work; References. … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2018
- Copyright Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 006.3/12
Computer science
Data mining in law enforcement -- Congresses
Social sciences -- Methodology -- Congresses
COMPUTERS -- Database Management -- Data Mining
Data mining in law enforcement
Social sciences -- Methodology
Operations Research, Management Science
Technology & Engineering -- Civil -- General
Business & Economics -- Operations Research
Highway & traffic engineering
Data mining
Operational research
Computer Communication Networks
Traffic Engineering
Data mining
Computers -- Hardware -- Network Hardware
Network hardware
Electronic books
Conference papers and proceedings - Languages:
- English
- ISBNs:
- 9783319756080
3319756087 - Related ISBNs:
- 9783319756073
3319756079 - Notes:
- Note: Includes bibliographical references and index.
Note: Online resource; title from PDF title page (EBSCO, viewed March 26, 2018). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.371004
- Ingest File:
- 02_351.xml