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Algorithms and Models for the Web-Graph

Overview of attention for book
Cover of 'Algorithms and Models for the Web-Graph'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Information Theoretic Comparison of Stochastic Graph Models: Some Experiments
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    Chapter 2 Approximating the Number of Network Motifs
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    Chapter 3 Finding Dense Subgraphs with Size Bounds
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    Chapter 4 The Giant Component in a Random Subgraph of a Given Graph
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    Chapter 5 Quantifying the Impact of Information Aggregation on Complex Networks: A Temporal Perspective
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    Chapter 6 A Local Graph Partitioning Algorithm Using Heat Kernel Pagerank
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    Chapter 7 Choose the Damping, Choose the Ranking?
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    Chapter 8 Characterization of Tail Dependence for In-Degree and PageRank
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    Chapter 9 Web Page Rank Prediction with PCA and EM Clustering
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    Chapter 10 Permuting Web Graphs
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    Chapter 11 A Dynamic Model for On-Line Social Networks
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    Chapter 12 TC-SocialRank: Ranking the Social Web
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    Chapter 13 Exploiting Positive and Negative Graded Relevance Assessments for Content Recommendation
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    Chapter 14 Cluster Based Personalized Search
Attention for Chapter 12: TC-SocialRank: Ranking the Social Web
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Citations

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Chapter title
TC-SocialRank: Ranking the Social Web
Chapter number 12
Book title
Algorithms and Models for the Web-Graph
Published by
Springer, Berlin, Heidelberg, February 2009
DOI 10.1007/978-3-540-95995-3_12
Book ISBNs
978-3-54-095994-6, 978-3-54-095995-3
Authors

Antonio Gulli, Stefano Cataudella, Luca Foschini

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 20%
Unknown 4 80%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 40%
Researcher 2 40%
Student > Master 1 20%
Readers by discipline Count As %
Computer Science 5 100%

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