Modelling and Mining Networks : 19th International Workshop, WAW 2024, Warsaw, Poland, June 3-6, 2024, Proceedings

• Autore: Dewar Megan
• Pubblicazione: Cham : , : Springer International Publishing AG, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (194 pages)
• Altri autori: KamińskiBogumił KaszyńskiDaniel KraińskiŁukasz PrałatPaweł ThébergeFrançois WrzosekMałgorzata
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Subgraph Counts in Random Clustering Graphs -- 1 Introduction -- 2 Preliminaries -- 2.1 Volumes -- 2.2 The Chung-Lu Model -- 2.3 Random Clustering Graphs -- 3 Extension Configurations -- 4 Subgraph Counts -- 5 Clustering Coefficient and Cycle Counts -- References -- Self-similarity of Communities of the ABCD Model -- 1 Introduction -- 2 The ABCD Model -- 2.1 Notation -- 2.2 The Configuration Model -- 2.3 Parameters of the ABCD Model -- 2.4 The ABCD Construction -- 2.5 A Known Result for ABCD -- 3 Main Result -- 4 Simulation Corner -- 4.1 The Coupling -- 4.2 Volumes of Communities -- 4.3 Self-loops and Multi-edges -- 5 Conclusion -- References -- A Simple Model of Influence: Details and Variants of Dynamics -- 1 Introduction -- 2 The Influencer Problem on the Cycle Cn -- 2.1 Results for the Cycle Cn -- 2.2 Analysis for the Cycle Cn -- 3 The Influencer Problem for Random Graphs G(n,p) -- 3.1 Results for G(n,p) When p=c/n -- 3.2 Analysis for Random Graphs G(n,p) -- 3.3 Random Edge -- 3.4 Basic Falling-Out Model -- 3.5 General Falling-Out Model -- 3.6 Formalizing the DE for w.h.p. Results -- 4 Conclusions and Further Work -- References -- Impact of Market Design and Trading Network Structure on Market Efficiency -- 1 Research Objective and Paper Structure -- 2 Definition of Research Problem and Its Motivation -- 3 Market Designs on Complete and Sparse Bipartite Graphs -- 3.1 Chamberlin's Higgling Market Vs Perfect Competition Model -- 3.2 Greedy Matching of Traders on Network -- 4 Simulation Results -- 4.1 Market Efficiency Drivers -- 4.2 Trade Participation Drivers -- 5 Conclusions and Further Research -- References -- Network Embedding Exploration Tool (NEExT) -- 1 Introduction -- 2 The Framework -- 2.1 Pre-processing -- 2.2 Vectorizing the Nodes -- 2.3 Embedding of the Graphs -- 3 Experiments. ; 3.1 Synthetic Graphs -- 3.2 Real-World Networks -- 4 Conclusion -- References -- Efficient Computation of K-Edge Connected Components: An Empirical Analysis -- 1 Introduction -- 2 Definitions -- 3 Related Work -- 4 Algorithms -- 4.1 Graph Decomposition Algorithm -- 4.2 Random Contraction Algorithm -- 4.3 Early Merging and Splitting -- 4.4 Local Cut Detection -- 5 Experiments -- 5.1 Small Graphs -- 5.2 Medium and Large Graphs -- 5.3 Evaluation of Optimization Techniques for RC -- 6 Discussion -- References -- The Directed Age-Dependent Random Connection Model with Arc Reciprocity -- 1 Motivation and Background -- 2 Model Introduction -- 2.1 The Directed Age-Dependent Random Connection Model -- 2.2 A Generative Model on Finite Domains and a Local Limit Procedure -- 3 Local Properties -- 3.1 Degree Distribution -- 3.2 Clustering -- 4 Directed Percolation -- References -- How to Cool a Graph -- 1 Introduction -- 2 Bounds on the Cooling Number -- 3 Isoperimetric Results and Grids -- 4 Cooling the ILT Model -- 5 Conclusion and Further Directions -- References -- Distributed Averaging for Accuracy Prediction in Networked Systems -- 1 Introduction -- 2 Background -- 2.1 Network Topology -- 2.2 Distributed Average -- 2.3 Gossip Algorithms -- 2.4 Convergence Rate and Accuracy -- 3 Proposed Approach -- 3.1 Problem Setup -- 3.2 Simulations -- 3.3 Local Graph Averages -- 3.4 Regression Models -- 3.5 Distributed Accuracy Prediction -- 4 Applications -- 4.1 Topology Changes -- 4.2 Anomaly Detection -- 5 Conclusion -- References -- Towards Graph Clustering for Distributed Computing Environments -- 1 Introduction -- 2 Model -- 3 Heuristic -- 4 Experiments -- 4.1 Performance on the Karate Graph -- 4.2 Performance on the ABCD Graph -- 4.3 Performance on a Road Network -- 5 Conclusions -- References. ; HypergraphRepository: A Community-Driven and Interactive Hypernetwork Data Collection -- 1 Introduction -- 2 Related Work -- 3 HypergraphRepository -- 3.1 Hypergraph Representations in HypergraphRepository -- 3.2 A Community-Driven Hypergraph Collection -- 3.3 An Interactive Hypergraph Repository -- 4 Conclusion -- References -- Clique Counts for Network Similarity -- 1 Introduction -- 2 Clique Profiles -- 3 Experimental Design and Methods -- 4 Discussion and Future Work -- References -- Author Index.
• Titolo autorizzato: Modelling and Mining Networks
• ISBN: 3-031-59205-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910855366303321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science Series