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{ "item_title" : "Algorithms and Models for the Web Graph", "item_author" : [" Konstantin Avrachenkov", "Pawel Pralat", "Nan Ye "], "item_description" : "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-R nyi 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. ", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/03/025/069/3030250695_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Algorithms and Models for the Web Graph|Konstantin Avrachenkov

Algorithms and Models for the Web Graph : 16th International Workshop, Waw 2019, Brisbane, Qld, Australia, July 6-7, 2019, Proceedings

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Overview

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-R nyi 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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Details

  • ISBN-13: 9783030250690
  • ISBN-10: 3030250695
  • Publisher: Springer
  • Publish Date: July 2019
  • Dimensions: 9.21 x 6.14 x 0.31 inches
  • Shipping Weight: 0.47 pounds
  • Page Count: 131

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