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|a 9783030250706
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|a Avrachenkov, Konstantin
|e [editor]
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|a Algorithms and Models for the Web Graph
|h Elektronische Ressource
|b 16th International Workshop, WAW 2019, Brisbane, QLD, Australia, July 6–7, 2019, Proceedings
|c edited by Konstantin Avrachenkov, Paweł Prałat, Nan Ye
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|a 1st ed. 2019
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|a Cham
|b Springer International Publishing
|c 2019, 2019
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|a IX, 131 p. 24 illus., 14 illus. in color
|b online resource
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|a Using Synthetic Networks for Parameter Tuning in Community Detection -- Efficiency of Transformations of Proximity Measures for Graph Clustering -- Almost Exact Recovery in Label Spreading -- Strongly n-e.c. Graphs and Independent Distinguishing Labellings -- The Robot Crawler Model on Complete k-Partite and Erdős-Rényi Random Graphs -- Estimating the Parameters of the Waxman Random Graph -- Understanding the Effectiveness of Data Reduction in Public Transportation Networks -- A Spatial Small-World Graph Arising from Activity-Based Reinforcement -- SimpleHypergraphs.jl - Novel Software Framework for Modelling and Analysis of Hypergraphs.
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|a Artificial intelligence / Data processing
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|a Computer graphics
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|a Computer science / Mathematics
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|a Discrete Mathematics in Computer Science
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|a Computer Graphics
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|a Artificial Intelligence
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|a Algorithms
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|a Artificial intelligence
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|a Discrete mathematics
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|a Data Science
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|a Prałat, Paweł
|e [editor]
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|a Ye, Nan
|e [editor]
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|a eng
|2 ISO 639-2
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|b Springer
|a Springer eBooks 2005-
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|a Theoretical Computer Science and General Issues
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|a 10.1007/978-3-030-25070-6
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|u https://doi.org/10.1007/978-3-030-25070-6?nosfx=y
|x Verlag
|3 Volltext
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|a 518.1
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|a This book constitutes the proceedings of the 16th International Workshop on Algorithms and Models for the Web Graph, WAW 2019, held in Brisbane, QLD, Australia, in July 2019. The 9 full papers presented in this volume were carefully reviewed and selected from 13 submissions. The papers cover topics of all aspects of algorithmic and mathematical research in the areas pertaining to the World Wide Web, espousing the view of complex data as networks
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