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Algorithms and Models for the Web Graph : 18th International Workshop, WAW 2023, Toronto, on, Canada, May 23-26, 2023, Proceedings / / Megan Dewar [and four others], editors
| Algorithms and Models for the Web Graph : 18th International Workshop, WAW 2023, Toronto, on, Canada, May 23-26, 2023, Proceedings / / Megan Dewar [and four others], editors |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (203 pages) |
| Disciplina | 005.1 |
| Collana | Lecture Notes in Computer Science Series |
| Soggetto topico |
Computer algorithms
Data mining World Wide Web |
| Soggetto non controllato |
Information Theory
Computer Science Computers |
| ISBN |
9783031322969
9783031322952 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Correcting for Granularity Bias in Modularity-Based Community Detection Methods -- 1 Introduction -- 2 Hyperspherical Geometry -- 3 The Heuristic -- 4 Derivation of the Heuristic -- 5 Experiments -- 6 Discussion -- References -- The Emergence of a Giant Component in One-Dimensional Inhomogeneous Networks with Long-Range Effects -- 1 Introduction and Statement of Result -- 1.1 The Weight-Dependent Random Connection Model -- 1.2 Main Result -- 1.3 Examples -- 2 Proof of the Main Theorem -- 2.1 Some Construction and Notation -- 2.2 Connecting Far Apart Vertex Sets -- 2.3 Existence of a Giant Component -- 2.4 Absence of an Infinite Component -- References -- Unsupervised Framework for Evaluating Structural Node Embeddings of Graphs -- 1 Introduction -- 2 Framework -- 2.1 Input/Output -- 2.2 Formal Description of the Algorithm -- 2.3 Properties -- 3 Experimentation -- 3.1 Synthetic Graphs Design -- 3.2 Algorithmic Properties of the Framework -- 3.3 Role Classification Case Study -- 4 Conclusion -- References -- Modularity Based Community Detection in Hypergraphs -- 1 Introduction -- 2 Modularity Functions -- 3 Hypergraph Modularity Optimization Algorithm -- 3.1 Louvain Algorithm -- 3.2 Challenges with Adjusting the Algorithm to Hypergraphs -- 3.3 Our Approach to Hypergraph Modularity Optimization: h-Louvain -- 4 Results -- 4.1 Synthetic Hypergraph Model: h-ABCD -- 4.2 Exhaustive Search for the Best Strategy -- 4.3 Comparing Basic Policies for Different Modularity Functions -- 5 Conclusions -- References -- Establishing Herd Immunity is Hard Even in Simple Geometric Networks -- 1 Introduction -- 2 Preliminaries -- 3 Unanimous Thresholds -- 4 Constant Thresholds -- 5 Majority Thresholds -- 6 Conclusions -- References -- Multilayer Hypergraph Clustering Using the Aggregate Similarity Matrix.
1 Introduction -- 2 Related Work -- 3 Algorithm and Main Results -- 4 Numerical Illustrations -- 5 Analysis of the Algorithm -- 5.1 SDP Analysis -- 5.2 Upper Bound on -- 5.3 Lower Bound on Dii -- 5.4 Assortativity -- 5.5 Proof of Theorem 1 -- 6 Conclusions -- References -- The Myth of the Robust-Yet-Fragile Nature of Scale-Free Networks: An Empirical Analysis -- 1 Introduction -- 2 Data -- 2.1 Network Collection -- 2.2 Network Categorization -- 2.3 Handling Weighted Networks -- 2.4 Preprocessing -- 3 Scale-Freeness Analysis -- 3.1 Scale-Freeness Classification Methods -- 3.2 Results -- 4 Robustness Analysis -- 4.1 Network Robustness -- 4.2 Configuration -- 4.3 Results -- 5 Conclusions -- 6 Appendix -- 6.1 Scale-Freeness Classification: Further Analysis -- 6.2 Robustness: Further Analysis -- 6.3 The Curious Case of Collins Yeast Interactome -- References -- A Random Graph Model for Clustering Graphs -- 1 Introduction -- 2 Preliminaries -- 3 Homomorphism Counts in the Chung-Lu Model -- 4 Random Clustering Graph Model -- 5 Homomorphism Counts -- 5.1 Extension Configurations -- 5.2 Expected Homomorphism Counts -- 5.3 Concentration of Subgraph Counts -- References -- Topological Analysis of Temporal Hypergraphs -- 1 Introduction -- 2 Method and Background -- 2.1 Temporal Hypergraphs -- 2.2 Sliding Windows for Hypergraph Snapshots -- 2.3 Associated ASC of a Hypergraph -- 2.4 Simplicial Homology -- 2.5 Zigzag Persistent Homology -- 3 Applications -- 3.1 Social Network Analysis -- 3.2 Cyber Data Analysis -- 4 Conclusion -- References -- PageRank Nibble on the Sparse Directed Stochastic Block Model -- 1 Introduction -- 2 Main Results -- 3 Proofs -- 4 Results from Simulations -- 5 Remarks and Conclusions -- References -- A Simple Model of Influence -- 1 Introduction -- 2 Analysis for Random Graphs G(n,m) -- 3 Proof of Lemma 1. 4 The Effect of Stubborn Vertices -- 5 The Largest Fragment in G(n,m) -- References -- The Iterated Local Transitivity Model for Tournaments -- 1 Introduction -- 2 Small World Property -- 3 Motifs and Universality -- 4 Graph-Theoretic Properties of the Models -- 4.1 Hamiltonicity -- 4.2 Spectral Properties -- 4.3 Domination Numbers -- 5 Conclusion and Further Directions -- References -- Author Index. |
| Record Nr. | UNISA-996534466403316 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Algorithms and Models for the Web Graph : 18th International Workshop, WAW 2023, Toronto, ON, Canada, May 23–26, 2023, Proceedings / / edited by Megan Dewar, Paweł Prałat, Przemysław Szufel, François Théberge, Małgorzata Wrzosek
| Algorithms and Models for the Web Graph : 18th International Workshop, WAW 2023, Toronto, ON, Canada, May 23–26, 2023, Proceedings / / edited by Megan Dewar, Paweł Prałat, Przemysław Szufel, François Théberge, Małgorzata Wrzosek |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (203 pages) |
| Disciplina | 005.1 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer science
Data structures (Computer science) Information theory Application software Computer science - Mathematics Discrete mathematics Computer networks Theory of Computation Data Structures and Information Theory Computer and Information Systems Applications Discrete Mathematics in Computer Science Computer Communication Networks |
| ISBN |
9783031322969
9783031322952 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Correcting for Granularity Bias in Modularity-Based Community Detection Methods -- The emergence of a giant component in one-dimensional inhomogeneous networks with long-range effects -- Unsupervised Framework for Evaluating Structural Node Embeddings of Graphs -- Modularity Based Community Detection in Hypergraphs -- Establishing Herd Immunity is Hard Even in Simple Geometric Networks -- Multilayer hypergraph clustering using the aggregate similarity matrix -- The Myth of the Robust-Yet-Fragile Nature of Scale-Free Networks: An Empirical Analysis -- A Random Graph Model for Clustering Graphs -- Topological Analysis of Temporal Hypergraphs -- PageRank Nibble on the sparse directed stochastic block model -- A simple model of influence -- The Iterated Local Transitivity Model for Tournaments. |
| Record Nr. | UNINA-9910725101403321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||