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Formalizing the concepts of crimes and criminals
Elzinga, P.G.
Publication date
2011
Link to publication
Citation for published version (APA):
Elzinga, P. G. (2011). Formalizing the concepts of crimes and criminals.
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CONTENTS
SUMMARY... I
CHAPTER 1 ...1
INTRODUCTION ...1
1.1 Concept Discovery...1
1.2 Intelligent-Led Policing, a historical overview...2
1.3 Intelligence-led policing and C-K modeling...3
1.3.1 3-i model of Ratcliffe...4
1.3.2 Concept Knowledge theory...4
1.4 Intelligence-led Policing and text mining...7
CHAPTER 2 ...9
Formal concept analysis in the literature...9
2.1 Introduction...9
2.2 Formal Concept Analysis...10
2.2.1. FCA essentials...10
2.2.2. FCA software...13
2.2.3. Web portal...13
2.3 Dataset...14
2.4 Studying the literature using FCA...14
2.4.1 Knowledge discovery and data mining...15
2.4.2 Information retrieval...17
2.4.3 Scalability...19
2.4.4 Ontologies...19
2.5 Conclusions...20
CHAPTER 3 ...23
Curbing domestic violence: Instantiating C-K theory with Formal Concept Analysis and Self Organizing Maps...23
3.1 Introduction...23
3.2 Intelligence Led Policing...26
3.2.1 Domestic violence...26
3.2.2 Motivation...28
3.3 FCA, ESOM and C-K theory...29
3.3.1 Formal Concept Analysis...29
3.3.2 Emergent Self Organizing Map...32
3.3.2.1 Emergent SOM...32
3.3.2.2 ESOM parameter settings...33
3.3.3 C-K theory...34
3.4 Instantiating C-K theory with FCA and ESOM...35
3.5 Dataset...38
3.5.1 Data pre-processing and feature selection...40
3.5.2 Initial classification performance...41
3.6 Iterative knowledge discovery with FCA and ESOM...42
3.6.1 Transforming existing knowledge into concepts...44
3.6.3 Transforming concepts into knowledge...53
3.6.4 Expanding the space of knowledge...56
3.7 Actionable results...58
3.8 Comparative study of ESOM and multi-dimensional scaling...65
3.9 Conclusions...69
CHAPTER 4 ...71
Formal concept analysis of temporal data...71
4.1 Terrorist threat assessment with Temporal Concept Analysis...71
4.1.1 Introduction...71
4.1.2 Backgrounder...72
4.1.2.1 Home-grown terrorism...72
4.1.2.2 The four phase model of radicalism...73
4.1.2.3 Current situation...74
4.1.3 Dataset...75
4.1.4 Temporal Concept Analysis...76
4.1.4.1 FCA essentials...76
4.1.4.2 TCA essentials...77
4.1.5 Research method...79
4.1.5.1 Extracting potential jihadists with FCA...79
4.1.5.2 Constructing Jihadism phases with FCA...81
4.1.5.3 Build detailed TCA lattice profiles for subjects...81
4.1.6 Conclusions...82
4.2 Identifying and profiling human trafficking and loverboy suspects....83
4.2.1 Introduction...83
4.2.2 Human trafficking and forced prostitution...84
4.2.2.1 Human trafficking model...84
4.2.2.2 Loverboy model...85
4.2.3 Dataset...86
4.2.4 Method...86
4.2.4.1 FCA analysis...87
4.2.4.2 Thesaurus...88
4.2.5 Analysis and results...89
4.2.5.1 ...90
Detection of suspects of human trafficking and forced prostitution 4.2.5.2 Case 1: Turkish human trafficking network...90
4.2.5.3 Case 2: Bulgarian male suspect...92
4.2.5.4 Case 3: Hungarian woman both victim and suspect...94
4.2.5.5 Case 4: Loverboy suspect...96
4.2.6 Discussion...97
4.2.7 Conclusions...100
CHAPTER 5 ...101
Concept Relation Discovery and Innovation Enabling Technology (CORDIET)101 5.1 Introduction...101
5.2 Data analysis artefacts...102
5.2.1 Formal Concept Analysis...102
5.2.3 Emergent Self Organising Maps...103
5.2.4 Hidden Markov Models...103
5.3 Data sources...103
5.3.1 Data source BVH...104
5.3.2 Data source scientific articles...104
5.3.3 Data source clinical pathways...105
5.4 Application domains...107
5.4.1 Domestic violence...107
5.4.2 Human trafficking...107
5.4.3 Terrorist threat assessment...108
5.4.4 Predicting criminal careers of suspects...109
5.5 CORDIET system architecture and business use case diagram...110
5.5.1 Business use case diagram...110
5.5.2 The software lifecycles of CORDIET...111
5.5.3 The development of an operational version of CORDIET...112
5.5.3.1 Presentation layer...112
5.5.3.2 Service...113
5.5.3.3 Business layer...113
5.5.3.4 Data access layer...113
5.5.3.5 Data...113
5.5.3.6 User interface...113
5.5.3.7 Language module...113
5.6 CORDIET functionality...113
5.6.1 K->C phase: start investigation...113
5.6.1.1 Load data sources...114
5.6.1.2 PostgreSQL database:...114
5.6.1.3 Lucene:...116
5.6.1.4 Create, load or modify ontology...116
5.6.1.5 Text mining attributes...118
5.6.1.6 Temporal attributes...118
5.6.1.7 Compound attributes...118
5.6.2 C->C phase: compose artefact...119
5.6.2.1 Select ontology...119
5.6.2.2 Define rules...119
5.6.2.2.1 Segmentation rules...120
5.6.2.2.2 Object cluster rules...120
5.6.2.2.3 Classifier rules...120
5.6.3 Choose and create artefact...121
5.6.3.1 C->K phase: analyze artefact...121
5.6.3.1.1 Detect object of interest...121
5.6.3.1.2 Detect anomaly...122
5.6.3.1.3 Detect knowledge concept...122
5.6.3.2 K->K phase: deploy knowledge product...122
5.7 Data and domain analysis scenarios...123
5.7.1 The functionality of the CORDIET toolbox...124
5.7.1.1.1 Ontology...125
5.7.1.1.2 Rule base...125
5.7.1.1.3 Summary report...126
5.7.1.1.4 Concept space options...126
5.7.1.1.5 TuProlog...126
5.7.1.1.6 ConExp...126
5.7.1.1.7 ESOM...126
5.7.1.1.8 Venn Diagramm...126
5.7.1.1.9 Tool menu options...127
5.7.1.1.10 Lucene index...127 5.7.1.1.11 Export RDBMS...128 5.7.1.1.12 Export Topicview...128 5.7.1.1.13 Export Topicmap...128 5.7.1.1.14 Export to HTML...128 5.7.2 ...129
Data analysis scenario “Create an ontology and a rule base for Domestic Violence” 5.7.2.1 K->C, prepare the datasets and create the ontology...129
5.7.2.1.1 Prepare the datasets...129
5.7.2.1.2 Create a new ontology...130
5.7.2.2 C->C: compose artefact...134
5.7.2.2.1 Select the ontology and rules...134
5.7.2.3 C->K analyze the artefacts...135
5.7.2.3.1 Analyze the initial results with a Venn diagram...135
5.7.2.3.2 Analyze the initial results with FCA lattices...136
5.7.2.3.3 Validate the ontology using FCA lattice...137
5.7.2.4 K->K: deploy new knowledge...139
5.7.2.5 Start a new C/K iteration...139
5.7.2.6 Validate the ontology using ESOM toroid map...141
5.7.2.7 C->C: compose the ESOM input files...143
5.7.2.8 C->C: Analyze the results of the ESOM map...145
5.7.2.9 K->K and K->C: update the ontology...146
5.7.2.10 ...147
C->C and C->K: compose new FCA input files and analyze the FCA lattices 5.7.2.11 K->K: deploy new knowledge...148
5.7.3 Domain analysis of human trafficking...148
5.7.3.1 Identify possible suspects and or victims...149
5.7.3.1.1 K->C: Create the signals ontology...149
5.7.3.1.2 C->C: compose the FCA lattices...150
5.7.3.1.3 C->K: analyze the FCA lattices...150
5.7.3.1.4 K->K: Creating a 27-construction report...157
5.7.4 Analyze the workforce intelligence of clinical pathways...158
5.7.4.1 Data sources...158
5.7.4.2 Ontology for workflow intelligence...159
5.7.4.3 Process variations...161
5.7.4.4 Analyzing the workflow intelligence...164
CHAPTER 6 ...169
Thesis conclusions ...169
6.1 Thesis conclusions...169
6.2 Future work...171
6.2.1 Terrorist threat assessment...171
6.2.2 Soloist threateners threat assessment...171
6.2.3 Human trafficking...172
6.2.4 Domestic violence...172
6.2.5 Improve the information quality of the BVH system...172
6.2.6 Financial Crime Analysis...172
6.2.7 Predicting crime careers...172
6.2.8 Supporting Large-scale investigation Teams...173
6.2.9 Intelligence Led Policing and Concept Discovery Toolset...173
SAMENVATTING...175
DANKWOORD ...185
PUBLICATIONS...187
APPENDIX A ...191
Literature survey thesaurus ...191
APPENDIX B ...193
Domestic violence case thesaurus ...193
APPENDIX C ...197
Human trafficking thesaurus ...197
APPENDIX D ...201
Simulating the Trueblue Domestic Violence rule ...201
APPENDIX E ...205
The rule based application ...205
APPENDIX F...211
Topicmap with FCA literature ontology examples ...211
APPENDIX H ...215
Human trafficking and Loverboy indicators ...215
APPENDIX I ...219
Excerpts of ESOM input files ...219
