Preface......Page 6
References......Page 9
Contents......Page 10
Contributors......Page 12
Network Algorithms......Page 15
1 Introduction......Page 16
1.1 Fairness in Communication Networks......Page 17
1.2 Fairness in Facility Location......Page 18
1.4 Fairness in Air Traffic Control (ATC)......Page 19
2 Fairness Early Development......Page 20
3.1 Basic Fairness Measures......Page 21
3.2 Gini Index......Page 22
3.4 Unfairness......Page 23
5 Max-Min Fairness......Page 24
6 Proportional Fairness......Page 26
7 (p, α) - Proportional Fairness......Page 27
8 Price of Fairness......Page 28
References......Page 29
Mixed Integer Programming for Searching Maximum Quasi-Bicliques......Page 32
2.1 Basic Definitions......Page 33
2.3 Maximum Quasi-Bicliques......Page 34
3.1 Model 1......Page 37
3.2 Model 2......Page 39
4 Datasets......Page 41
5.1 Implementation Description......Page 42
5.2 Illustrative Examples......Page 43
5.3 Comparison of Algorithms......Page 44
6 Results and Conclusions......Page 45
References......Page 47
1 Introduction......Page 49
2 Previous Work......Page 51
3 Problem Formulation......Page 52
3.1 Optimization Problem: Mean Intra-Cluster Density Maximization......Page 53
3.2 Overcoming Common Degeneracies......Page 54
4.1 Meta-Heuristic Techniques......Page 56
4.2 Preliminary Results......Page 58
References......Page 59
1 Introduction......Page 61
2.2 Short-Range Interaction Centrality (SRIC)......Page 63
2.3 Long-Range Interaction Centrality (LRIC)......Page 65
3.1 Computational Complexity of the SRIC Index......Page 67
3.2 Computational Complexity of the LRIC Index......Page 69
4 Experimental Results......Page 77
4.1 Experimental Results on Complete Graphs......Page 78
4.2 Experimental Results on Complete Graphs......Page 79
5 Conclusion......Page 80
References......Page 81
1 Introduction......Page 83
2 Variable Neighborhood Search......Page 84
3.1 VNS for the ELSR......Page 85
3.3 VNS for MLLSs......Page 86
3.5 VNS for IRPs......Page 87
3.8 VNS for Sustainable Order Allocation (inventory) and Sustainable Supply Chain......Page 89
3.11 VNS for Vendor Managed Inventory Problems......Page 90
5 Future Research Guidelines......Page 91
References......Page 93
Network Data Mining......Page 95
GSM: Inductive Learning on Dynamic Graph Embeddings......Page 96
1 Introduction......Page 97
2 Notation and Basic Definitions......Page 98
3.1 Matrix Factorization Based Methods......Page 100
3.2 Random Walk Based Methods......Page 101
4 Inductive Learning Embeddings on Dynamic Graphs......Page 102
5.1 Baseline......Page 103
5.2 Datasets......Page 104
5.3 Model Framework......Page 105
5.5 Discussion......Page 107
References......Page 108
Collaborator Recommender System......Page 111
1 Introduction and Related Work......Page 112
3 Data Description......Page 114
4 Model Description......Page 117
5 Results......Page 121
6 Conclusion......Page 124
7 Appendix......Page 125
References......Page 129
1 Introduction......Page 130
2 Decision-Making Using Neural Aggregation of Visual Data......Page 131
3 Experimental Results......Page 132
References......Page 135
1 Introduction......Page 137
2 Related Work......Page 138
3 Wikipedia Network Creation......Page 139
4 Analysis of Nodes degree Distribution for Article Nodes......Page 141
5 Methods for Clearing Diffusion of Tails of Nodes Degree Distributions......Page 144
6 Elimination of the Source of Deviation for Out-Degree Probability Density Function......Page 146
References......Page 149
1 Introduction......Page 151
2 Literature Review......Page 152
3 Long-Range Interaction Centrality (LRIC)......Page 154
4 Data Analysis and Results......Page 159
References......Page 167
1 Introduction......Page 169
2 Video Data Analysis......Page 170
3 Experimental Results......Page 173
References......Page 177
Network Applications......Page 179
1 Introduction......Page 180
2 Auxiliary Assertions......Page 181
3 The Main Result......Page 183
4 The Properties of the Studied Class of Integro-Differential Equations......Page 190
References......Page 192
1.1 Description of the Research Problem......Page 194
1.2 Research Problems of Information Gathering on Social Networks in the KChR......Page 195
2.1 Network Approaches to Regional Political Mapping on the Internet......Page 196
2.2 Regional Policy Network Studies......Page 197
3 A Brief Description of the Mapping of Social Networks Using Grain Clustering Algorithm......Page 198
4.1 General Clustering of Groups that Show Political Activity in the Information Space of the KChR and Neighboring Caucasian Regions......Page 200
4.2 Cluster of Politically Active Groups of KChR......Page 202
5 Conclusion......Page 203
References......Page 206
1 Introduction......Page 208
2.1 Approaches in the Modern Conceptual Analysis......Page 210
2.2 Expert Analysis of the “Digital Economy” Field Formation......Page 211
3.1 Toolkit for the Text Analysis......Page 213
3.2 Conceptual Statistical Analysis of Texts......Page 214
4 Empirical Results......Page 216
5 Conclusion......Page 220
References......Page 222
1 Introduction......Page 225
2.1 Theoretical Background for the Study of Discourse......Page 226
2.3 Linguistic Features of Measuring Distinctive Words......Page 227
3.1 Data Description......Page 228
3.3 Methodological Issues......Page 229
4 Practical Results of the Study......Page 230
5.1 Informative Conclusions......Page 234
5.3 Final Thoughts......Page 235
References......Page 236
1 Introduction......Page 237
2 Methodology......Page 239
3 Application......Page 244
References......Page 249