Algorithms and Models for the Web Graph - Info and Reading Options

Open Data:

Intro -- Preface -- Organization -- Contents -- Using Synthetic Networks for Parameter Tuning in Community Detection -- 1 Introduction -- 2 Background and Related Work -- 2.1 Modularity -- 2.2 Modularity Optimization and Louvain Algorithm -- 2.3 Likelihood Optimization Methods -- 2.4 LFR Model -- 3 Tuning Parameters -- 4 Experiments -- 4.1 Parametric Algorithms -- 4.2 Datasets -- 4.3 Evaluation Metrics -- 4.4 Experimental Setup -- 4.5 Results -- 5 Conclusion -- References -- Efficiency of Transformations of Proximity Measures for Graph Clustering -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Definitions -- 3.2 Kernels -- 3.3 Transformations -- 4 Experiments and Results -- 4.1 Experimental Methodology -- 4.2 Analysis -- 4.3 Examining the Results by Friedman and Nemenyi Tests -- 5 Conclusion -- References -- Almost Exact Recovery in Label Spreading -- 1 Introduction and Previous Work -- 2 Semi-supervised Graph Clustering with the Normalized Laplacian Matrix (Label Spreading) -- 3 Analysis on Random SBM Graphs -- 3.1 Exact Expression for Mean Field SBM -- 3.2 Concentration Towards Mean Field -- 3.3 Asymptotically Almost Exact Recovery for SBM -- 4 Discussion and Future Works -- A Background Results on Matrix Analysis -- A.1 Inversion of the Identity Matrix Minus a Rank 2 Matrix -- A.2 Spectral Study of a Rank 2 Matrix -- A.3 Spectral Study of EL -- B Spectral Norm of an Extracted Matrix -- References -- Strongly n-e.c. Graphs and Independent Distinguishing Labellings -- 1 Introduction -- 2 Constructing Infinite Graphs by (n)-extensions -- 3 Constructing Infinite Graphs by (n)-extensions -- 4 An Application of the Strong e.c. Property to Graph Distinguishing -- 5 Conclusion -- References -- The Robot Crawler Model on Complete k-Partite and Erdős-Rényi Random Graphs -- 1 Introduction -- 2 Erdős-Rényi Random Graph

Search for “Algorithms and Models for the Web Graph” downloads:

Visit our Downloads Search page to see if downloads are available.

Find “Algorithms and Models for the Web Graph” in Libraries Near You:

Read or borrow “Algorithms and Models for the Web Graph” from your local library.

• The WorldCat Libraries Catalog: Find a copy of “Algorithms and Models for the Web Graph” at a library near you.