Complex networks: an algorithmic perspective
"Network science is an emerging field of study that encompasses mathematics, computer science, physics, and engineering. An important issue in the study of complex networks is to understand the collective behavior of the elements of these networks. Although the results from graph theory have pr...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton
CRC Press
2017
|
| Ausgabe: | First issued in paperback |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | "Network science is an emerging field of study that encompasses mathematics, computer science, physics, and engineering. An important issue in the study of complex networks is to understand the collective behavior of the elements of these networks. Although the results from graph theory have proven to be powerful in investigating the structures of complex networks, there are few books on the algorithmic aspects of complex network analysis. Filling this need, this book supplies the basic theoretical algorithmic and graph theoretic knowledge needed by every researcher of complex networks".. |
| Beschreibung: | xxv, 294 Seiten Illustrationen 24 cm |
| ISBN: | 9781138033894 |
Internformat
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| 520 | |a "Network science is an emerging field of study that encompasses mathematics, computer science, physics, and engineering. An important issue in the study of complex networks is to understand the collective behavior of the elements of these networks. Although the results from graph theory have proven to be powerful in investigating the structures of complex networks, there are few books on the algorithmic aspects of complex network analysis. Filling this need, this book supplies the basic theoretical algorithmic and graph theoretic knowledge needed by every researcher of complex networks".. | ||
| 650 | 7 | |a COMPUTERS / Networking / General |2 bisacsh | |
| 650 | 7 | |a COMPUTERS / Operating Systems / General |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS / Arithmetic |2 bisacsh | |
| 650 | 4 | |a Mathematik | |
| 650 | 4 | |a System analysis |x Mathematics | |
| 650 | 4 | |a Computational complexity | |
| 650 | 4 | |a Algorithms | |
| 650 | 4 | |a COMPUTERS / Networking / General | |
| 650 | 4 | |a COMPUTERS / Operating Systems / General | |
| 650 | 4 | |a MATHEMATICS / Arithmetic | |
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Datensatz im Suchindex
| _version_ | 1804178745727123456 |
|---|---|
| adam_text | Contents
List of Figures....................................................... xv
List of Tables....................................................... xxi
Preface.............................................................xxiii
1 Introduction........................................................ 1
1.1 Overview....................................................... 1
1.2 Real-world Complex Networks ................................... 2
L2.1 Technological Networks.................................. 2
L2.2 Information Networks.................................... 3
L2.3 Social Networks......................................... 3
L2.4 Biological Networks .................................... 4
1.3 Topological Properties of Complex Networks..................... 5
1.4 Algorithmic Challenges ........................................ 6
1.5 Outline of the Book ........................................... 7
References ........................................................ 7
SECTION I: BACKGROUND 9
2 Graph Theory....................................................... 11
2.1 Basics........................................................ 11
2.2 Subgraphs .................................................... 12
2.3 Graph Isomorphism ......................................... . 13
2.4 Types of Graphs .............................................. 14
2.5 Paths and Cycles.............................................. 15
2.6 Connectivity ................................................. 16
2.7 Trees ........................................................ 18
2.8 Graph Representations......................................... 19
vii
viii ■ Contents
2.9 Spectral Properties of Graphs ................................... 19
2.9.1 Eigenvalues and Eigenvectors............................. 20
2.9.2 The Laplacian Matrix..................................... 21
2.10 Chapter Notes .................................................. 22
References ........................................................... 24
3 Algorithms and Complexity............................................ 27
3.1 Introduction..................................................... 27
3.2 Time Complexity.................................................. 29
3.3 Recurrences...................................................... 31
3.4 Divide and Conquer Algorithms.................................... 32
3.5 Graph Algorithms ................................................ 33
3.5.1 Breadth-first Search .................................... 34
3.5.2 Depth-first Search....................................... 36
3.6 Dynamic Programming.............................................. 37
3.7 Greedy Algorithms................................................ 39
3.8 NP-complete Problems............................................. 41
3.8.1 NP Completeness.......................................... 41
3.8.2 Reductions............................................... 43
3.8.2.1 Satisfiability Problems......................... 44
3.8.2.2 3-SAT to Independent Set........................ 45
3.8.2.3 Independent Set to Vertex Cover................. 45
3.8.2.4 Independent Set to Clique....................... 46
3.9 Coping with NP Completeness...................................... 48
3.9.1 Backtracking............................................. 48
3.9.2 Branch and Bound......................................... 49
3.10 Approximation Algorithms........................................ 50
3.11 Parallel Algorithms............................................. 53
3.11.1 Architectural Constraints................................ 54
3.11.2 Example Algorithms....................................... 54
3.12 Distributed Systems and Algorithms.............................. 57
3.13 Chapter Notes .................................................. 59
References ........................................................... 61
4 Analysis of Complex Networks.......................................... 63
4.1 Introduction..................................................... 63
4.2 Vertex Degrees................................................... 64
4.2.1 Degree Sequence.......................................... 65
4.2.2 Degree Distribution...................................... 66
4.3 Communities...................................................... 67
4.3.1 Clustering Coefficient................................... 68
4.4 The Matching Index .............................................. 70
4.5 Centrality....................................................... 70
4.6 Network Motifs................................................... 71
4.7 Models ......................................................... 72
Contents ■ ix
4.7.1 Classical Random Networks............................... 72
4.7.2 Small World Networks.................................... 72
4.7.3 Scale-Free Networks..................................... 73
4.8 Chapter Notes ................................................. 75
References ......................................................... 77
SECTION II: ALGORITHMS 79
5 Distance and Centrality.............................................. 81
5.1 Introduction.................................................. 81
5.2 Finding Distances ............................................. 81
5.2.1 Average Distance........................................ 83
5.2.2 Dijkstra’s Single Source Shortest Paths Algorithm....... 83
5.2.3 Floyd-Warshall All Pairs Shortest Paths Algorithm....... 84
5.3 Centrality..................................................... 87
5.3.1 Degree Centrality....................................... 87
5.3.1.1 A Distributed Algorithm for -hop Degree Cen-
trality ................................................ 89
5.3.2 Closeness Centrality.................................... 91
5.3.3 Stress Centrality....................................... 92
5.3.4 Betweenness Centrality.................................. 93
5.3.4.1 Newman’s Algorithm............................. 94
5.3.4.2 Brandes’ Algorithm............................. 95
5.3.5 Eigenvalue Centrality................................... 96
5.4 Chapter Notes ................................................. 97
References ......................................................... 99
6 Special Subgraphs................................................... 101
6.1 Introduction.................................................. 101
6.2 Maximal Independent Sets...................................... 102
6.3 Dominating Sets .............................................. 103
6.3.1 A Greedy MDS Algorithm................................. 105
6.3.2 Guha-Khuller First MCDS Algorithm...................... 106
6.3.3 Guha-Khuller Second MCDS Algorithm..................... 106
6.4 Matching...................................................... 108
6.4.1 A Maximal Unweighted Matching Algorithm................ 109
6.4.2 A Maximal Weighted Matching Algorithm.................. 109
6.5 Vertex Cover.................................................. 110
6.5.1 A Minimal Connected Vertex Cover Algorithm............. 112
6.5.2 A Minimal Weighted Vertex Cover Algorithm.............. 113
6.6 A Distributed Algorithm for MWVC Construction ................ 114
6.7 Chapter Notes ................................................ 116
References ........................................................ 118
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■ Contents
Data Clustering............................
7.1 Introduction.........................
7.2 Types of Data Clustering.............
7.3 Agglomerative Hierarchical Clustering
7.4 ¿-means Algorithm....................
7.5 Nearest Neighbor Algorithm...........
7.6 Fuzzy Clustering.....................
7.7 Density-based Clustering.............
7.8 Parallel Data Clustering ............
7.9 Chapter Notes ...................
References ................................
Graph-based Clustering.....................
8.1 Introduction.........................
8.2 Graph Partitioning ..................
8.2.1 BFS-based Partitioning........
8.2.2 Kemighan-Lin Algorithm . . .
8.2.3 Spectral Bisection............
8.2.4 Multi-level Partitioning......
8.2.5 Parallel Partitioning.........
8.3 Graph Clustering.....................
8.3.1 MST-based Clustering..........
8.3.2 Clustering with Clusterheads . .
8.4 Discovery of Dense Subgraphs.........
8.4.1 Definitions...................
8.4.2 Clique Algorithms.............
8.4.2.1 The First Algorithm .
8.4.2.2 The Second Algorithm
8.4.3 ¿-core Algorithm..............
8.5 Chapter Notes .......................
References ................................
Network Motif Discovery....................
9.1 Introduction.........................
9.2 Network Motifs.......................
9.2.1 Measures of Motif Significance
9.2.2 Generating Null Models ....
9.2.3 Hardness of Motif Discovery . .
9.3 Subgraph Isomorphism.................
9.3.1 Vertex Invariants.............
9.3.2 Algorithms....................
9.3.2.1 Ullman’s Algorithm .
9.3.2.2 Nauty Algorithm . .
9.3.2.3 VF2 Algorithm . . .
9.3.2.4 BM1 Algorithm . . .
Contents ■ xi
9.4 Motif Discovery Algorithms................................... 181
9.4.1 Exact Census Algorithms............................... 182
9.4.1.1 Mfinder Algorithm............................ 182
9.4.1.2 Enumerate Subgraphs (ESU) Algorithm.......... 183
9.4.1.3 Grochow and Kellis Algorithm................. 184
9.4.1.4 Kavosh Algorithm............................. 186
9.4.1.5 MODA......................................... 188
9.4.2 Approximate Algorithms with Sampling.................. 190
9.4.2.1 Mfinder with Sampling........................ 191
9.4.2.2 Randomized ESU Algorithm..................... 192
9.4.2.3 MODA with Sampling........................... 194
9.5 Chapter Notes ............................................... 194
References ....................................................... 197
SECTION III:APPLICATIONS 201
10 Protein Interaction Networks........................................203
10.1 Introduction..................................................203
10.2 Topological Properties of PPI Networks........................204
10.3 Detection of Protein Complexes................................206
10.3.1 Highly Connected Subgraphs Algorithm...................206
10.3.2 Restricted Neighborhood Search Algorithm...............207
10.3.3 Molecular Complex Detection Algorithm..................208
10.3.4 Markov Clustering Algorithm............................209
10.4 Network Motifs in PPI Networks ...............................211
10.5 Network Alignment ............................................214
10.5.1 Quality of the Alignment . . ..........................216
10.5.1.1 Topological Similarity........................216
10.5.1.2 Node Similarity...............................216
10.5.2 Algorithms.............................................217
10.5.2.1 PathBLAST.....................................217
10.5.2.2 MaWIsh........................................217
10.5.2.3 IsoRank.......................................218
10.5.2.4 GRAAL.........................................219
10.5.2.5 Recent Algorithms.............................220
10.6 Chapter Notes ................................................220
References .................................................... 223 11
11 Social Networks.....................................................227
11.1 Introduction..................................................227
11.2 Relationships.................................................228
11.2.1 Homophily...............................................228
11.2.2 Positive and Negative Relations.........................229
11.2.3 Structural Balance......................................230
11.3 Equivalence...................................................232
xii ■ Contents
11.4 Community Detection Algorithms...................................233
11.4.1 Edge Betweenness-based Algorithm..........................233
11.4.2 Resistor Networks.........................................237
11.4.3 Random Walk Centrality....................................238
11.4.4 Modularity-based Algorithm ...............................239
11.5 Chapter Notes ...................................................241
References ...........................................................244
12 The Internet and the Web..............................................245
12.1 Introduction.....................................................245
12.2 The Internet.....................................................245
12.2.1 Services..................................................246
12.2.1.1 Services of Connection..........................246
12.2.1.2 Circuit and Packet Switching....................247
12.2.1.3 Internet Protocol Suite.........................247
12.2.2 Analysis .................................................248
12.3 The Web ........................................................ 249
12.3.1 The Web Graph.............................................250
12.3.1.1 Properties......................................251
12.3.1.2 Evolving Model..................................253
12.3.1.3 Copying Model...................................253
12.3.1.4 Growthrdeletion Model...........................254
12.3.1.5 Multi-layer Model........................... 254
12.3.1.6 Cyber Community Detection.......................255
12.3.2 Link Analysis.............................................256
12.3.2.1 Hubs and Authorities............................256
12.3.2.2 Page Rank Algorithm.............................259
12.4 Chapter Notes ................................................. 263
References ...........................................................265
13 Ad hoc Wireless Networks .............................................269
13.1 Introduction.....................................................269
13.2 Clustering Algorithms .......................................... 271
13.2.1 Lowest-ID Algorithm.......................................271
13.2.2 Dominating Set-based Clustering...........................273
13.2.3 Spanning Tree-based Clustering............................275
13.3 Mobile Social Networks ..........................................277
13.3.1 Architecture............................................ 278
13.3.2 Community Detection.......................................278
13.3.3 Middleware................................................281
13.3.3.1 MobiSoC.........................................282
13.3.3.2 MobiClique......................................282
13.3.3.3 SAMOA...........................................283
13.3.3.4 Yarta...........................................284
13.4 Chapter Notes .................................................. 285
Contents ■ xiii
References
287
Index
291
|
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| discipline | Informatik Mathematik |
| edition | First issued in paperback |
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| indexdate | 2024-07-10T08:08:51Z |
| institution | BVB |
| isbn | 9781138033894 |
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| physical | xxv, 294 Seiten Illustrationen 24 cm |
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| publisher | CRC Press |
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| spelling | Erciyes, Kayhan Verfasser (DE-588)109591362X aut Complex networks an algorithmic perspective Kayhan Erciyes First issued in paperback Boca Raton CRC Press 2017 xxv, 294 Seiten Illustrationen 24 cm txt rdacontent n rdamedia nc rdacarrier "Network science is an emerging field of study that encompasses mathematics, computer science, physics, and engineering. An important issue in the study of complex networks is to understand the collective behavior of the elements of these networks. Although the results from graph theory have proven to be powerful in investigating the structures of complex networks, there are few books on the algorithmic aspects of complex network analysis. Filling this need, this book supplies the basic theoretical algorithmic and graph theoretic knowledge needed by every researcher of complex networks".. COMPUTERS / Networking / General bisacsh COMPUTERS / Operating Systems / General bisacsh MATHEMATICS / Arithmetic bisacsh Mathematik System analysis Mathematics Computational complexity Algorithms COMPUTERS / Networking / General COMPUTERS / Operating Systems / General MATHEMATICS / Arithmetic Netzwerk Graphentheorie (DE-588)4705155-3 gnd rswk-swf Algorithmus (DE-588)4001183-5 gnd rswk-swf Netzwerk Graphentheorie (DE-588)4705155-3 s Algorithmus (DE-588)4001183-5 s DE-604 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030497717&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Erciyes, Kayhan Complex networks an algorithmic perspective COMPUTERS / Networking / General bisacsh COMPUTERS / Operating Systems / General bisacsh MATHEMATICS / Arithmetic bisacsh Mathematik System analysis Mathematics Computational complexity Algorithms COMPUTERS / Networking / General COMPUTERS / Operating Systems / General MATHEMATICS / Arithmetic Netzwerk Graphentheorie (DE-588)4705155-3 gnd Algorithmus (DE-588)4001183-5 gnd |
| subject_GND | (DE-588)4705155-3 (DE-588)4001183-5 |
| title | Complex networks an algorithmic perspective |
| title_auth | Complex networks an algorithmic perspective |
| title_exact_search | Complex networks an algorithmic perspective |
| title_full | Complex networks an algorithmic perspective Kayhan Erciyes |
| title_fullStr | Complex networks an algorithmic perspective Kayhan Erciyes |
| title_full_unstemmed | Complex networks an algorithmic perspective Kayhan Erciyes |
| title_short | Complex networks |
| title_sort | complex networks an algorithmic perspective |
| title_sub | an algorithmic perspective |
| topic | COMPUTERS / Networking / General bisacsh COMPUTERS / Operating Systems / General bisacsh MATHEMATICS / Arithmetic bisacsh Mathematik System analysis Mathematics Computational complexity Algorithms COMPUTERS / Networking / General COMPUTERS / Operating Systems / General MATHEMATICS / Arithmetic Netzwerk Graphentheorie (DE-588)4705155-3 gnd Algorithmus (DE-588)4001183-5 gnd |
| topic_facet | COMPUTERS / Networking / General COMPUTERS / Operating Systems / General MATHEMATICS / Arithmetic Mathematik System analysis Mathematics Computational complexity Algorithms Netzwerk Graphentheorie Algorithmus |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030497717&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT erciyeskayhan complexnetworksanalgorithmicperspective |