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Network role mining and analysis [electronic resource]

Network role mining and analysis [electronic resource]

Material type
E-Book(소장)
Personal Author
Doran, Derek.
Title Statement
Network role mining and analysis [electronic resource] / Derek Doran.
Publication, Distribution, etc
Cham :   Springer,   c2017.  
Physical Medium
1 online resource (xi, 101 p.) : ill. (some col.).
Series Statement
SpringerBriefs in complexity,2191-5326, 2191-5334 (electronic)
ISBN
9783319538860 (e-book) 9783319538853
요약
This brief presents readers with a summary of classic, modern, and state-of-the-art methods for discovering the roles of entities in networks (including social networks) that range from small to large-scale. It classifies methods by their mathematical underpinning, whether they are driven by implications about entity behaviors in system, or if they are purely data driven. The brief also discusses when and how each method should be applied, and discusses some outstanding challenges toward the development of future role mining methods of each type.
General Note
Title from e-Book title page.  
Content Notes
Network Role Mining and Analysis: An Overview -- Implied Role Mining -- Equivalence-Based Role Mining -- Deterministic Blockmodeling -- Stochastic Blockmodeling -- Advanced Computational Methods -- Concluding Remarks.
Bibliography, Etc. Note
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Data mining. Big data. Consciousness.
Short cut
URL
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020 ▼a 9783319538860 (e-book)
020 ▼a 9783319538853
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050 4 ▼a QA76.9.D343
082 0 4 ▼a 006.312 ▼2 23
084 ▼a 006.312 ▼2 DDCK
090 ▼a 006.312
100 1 ▼a Doran, Derek.
245 1 0 ▼a Network role mining and analysis ▼h [electronic resource] / ▼c Derek Doran.
260 ▼a Cham : ▼b Springer, ▼c c2017.
300 ▼a 1 online resource (xi, 101 p.) : ▼b ill. (some col.).
490 1 ▼a SpringerBriefs in complexity, ▼x 2191-5326, ▼x 2191-5334 (electronic)
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
505 0 ▼a Network Role Mining and Analysis: An Overview -- Implied Role Mining -- Equivalence-Based Role Mining -- Deterministic Blockmodeling -- Stochastic Blockmodeling -- Advanced Computational Methods -- Concluding Remarks.
520 ▼a This brief presents readers with a summary of classic, modern, and state-of-the-art methods for discovering the roles of entities in networks (including social networks) that range from small to large-scale. It classifies methods by their mathematical underpinning, whether they are driven by implications about entity behaviors in system, or if they are purely data driven. The brief also discusses when and how each method should be applied, and discusses some outstanding challenges toward the development of future role mining methods of each type.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Data mining.
650 0 ▼a Big data.
650 0 ▼a Consciousness.
830 0 ▼a SpringerBriefs in complexity.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=https://doi.org/10.1007/978-3-319-53886-0
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 006.312 Accession No. E14018610 Availability Loan can not(reference room) Due Date Make a Reservation Service M

Contents information

Table of Contents

CONTENTS
1 Network Role Mining and Analysis : An Overview = 1
 1.1 Introduction = 1
 1.2 Denning Roles = 2
  1.2.1 Networks = 3
  1.2.2 Positions in Networks = 5
 1.3 Mining Roles = 6
  1.3.1 Relationship to Graph Partitioning and Community Detection = 10
 1.4 Purpose and Outline of This Monograph = 11
 References = 11
2 Implied Role Mining = 15
 2.1 Introduction = 15
 2.2 The Implied Role Mining Process = 17
 2.3 Illustrations with Usenet = 18
  2.3.1 Golder et al.''''s Taxonomy = 19
  2.3.2 Nolker et al.''''s Hierarchy = 22
 2.4 Analysis of Implied Role Mining = 25
  2.4.1 Qualitative Nature = 25
  2.4.2 Compatibility = 26
  2.4.3 Simplicity and Interpretability = 27
 2.5 Conclusion = 29
 References = 30
3 Equivalence-Based Role Mining = 31
 3.1 Introduction = 31
 3.2 Structural Equivalence = 32
  3.2.1 Finding Structural Equivalences = 32
 3.3 Automorphic Equivalence = 34
  3.3.1 Finding Automorphic Equivalences = 35
  3.3.2 Quantifying Automorphic Similarity = 37
 3.4 Regular Equivalence = 40
  3.4.1 Finding Regular Equivalences = 40
  3.4.2 Quantifying Regular Similarity = 45
 3.5 Conclusion = 46
 References = 46
4 Deterministic Blockmodeling = 49
 4.1 Introduction = 49
 4.2 The Blockmodeling Framework = 52
  4.2.1 Similarity Measures = 52
  4.2.2 Blocktypes = 56
 4.3 Goodness of Fit = 58
  4.3.1 A Goodness-of-Fit Measure for Positional Analysis = 59
  4.3.2 A Goodness-of-Fit Measure for Network Compression = 60
 4.4 Conclusion = 60
 References = 61
5 Stochastic Blockmodeling = 63
 5.1 Introduction = 63
 5.2 SBM Specification = 64
 5.3 The Infinite Relational Model = 65
  5.3.1 Parameter Inference for the IRM = 67
  5.3.2 Summary = 70
 5.4 The Dynamic Stochastic Blockmodel = 70
  5.4.1 DSBM Network Generation = 71
  5.4.2 Parameter Inference for the DSBM = 73
 5.5 Conclusion = 75
 References = 75
6 Advanced Computational Methods = 77
 6.1 Factor Graphs : The Social Roles and Statuses Factor Graph Model = 78
  6.1.1 Social Features = 79
  6.1.2 A Factor Graph Model = 80
 6.2 Multi-view Learning : Dual-View Uncertainty Regularization = 82
  6.2.1 Graph Co-regularization = 83
  6.2.2 Uncertainty Regularization and Objective Function = 84
 6.3 Bayesian Modeling : Co-discovery of Roles in Communities = 85
 6.4 Matrix Factorization : RolX = 87
 6.5 Iterative Quadratic Programming : Synergistic Co-discovery of Communities and Roles = 89
  6.5.1 Initializing Communities (InitCom) = 90
  6.5.2 Initializing Roles (InitRole) = 90
  6.5.3 Updating Communities = 91
  6.5.4 Updating Roles = 92
 6.6 Conclusion = 92
 References = 93
7 Concluding Remarks = 95
 7.1 Emerging Trends in Role Mining = 96
 7.2 Tension Between Rigor and Interpretability = 98
 References = 100

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