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Centrality and Diversity in Search

Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition

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  • © 2019

Overview

Authors:
  1. M.N. Murty

    1. Department of Computer Science and Automation, Indian Institute of Science, Bengaluru, India

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    You can also search for this author in PubMed   Google Scholar

  2. Anirban Biswas

    1. Department of Computer Science and Automation, Indian Institute of Science, Bengaluru, India

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    You can also search for this author in PubMed   Google Scholar

  • Presents a detailed examination of the role of centrality and diversity in search
  • Discusses tasks in machine learning, data mining, pattern recognition, and information retrieval
  • Describes applications in social and information networks

Part of the book series: SpringerBriefs in Intelligent Systems (BRIEFSINSY)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xi
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  2. Introduction

    • M. N. Murty, Anirban Biswas
    Pages 1-12

  3. Searching

    • M. N. Murty, Anirban Biswas
    Pages 13-28

  4. Representation

    • M. N. Murty, Anirban Biswas
    Pages 29-47

  5. Clustering and Classification

    • M. N. Murty, Anirban Biswas
    Pages 49-63

  6. Ranking

    • M. N. Murty, Anirban Biswas
    Pages 65-69

  7. Centrality and Diversity in Social and Information Networks

    • M. N. Murty, Anirban Biswas
    Pages 71-86

  8. Conclusion

    • M. N. Murty, Anirban Biswas
    Pages 87-87

  9. Back Matter

    Pages 89-94
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Keywords

About this book

The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition. This work examines the significance of centrality and diversity in representation, regression, ranking, clustering, optimization, and classification.

The text is designed to be accessible to a broad readership. Requiring only a basic background in undergraduate-level mathematics, the work is suitable for senior undergraduate and graduate students, as well as researchers working in machine learning, data mining, social networks, and pattern recognition.

 

Authors and Affiliations

  • Department of Computer Science and Automation, Indian Institute of Science, Bengaluru, India

    M.N. Murty, Anirban Biswas

About the authors

Dr. M.N. Murty is a Professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore, India. Anirban Biswas is a Teaching Assistant at the same institution.

Prof. Murty’s other publications include the Springer titles Support Vector Machines and Perceptrons, Compression Schemes for Mining Large Datasets, and Pattern Recognition: An Algorithmic Approach.

Bibliographic Information

  • Book Title: Centrality and Diversity in Search

  • Book Subtitle: Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition

  • Authors: M.N. Murty, Anirban Biswas

  • Series Title: SpringerBriefs in Intelligent Systems

  • DOI: https://doi.org/10.1007/978-3-030-24713-3

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG, part of Springer Nature 2019

  • Softcover ISBN: 978-3-030-24712-6Published: 24 August 2019

  • eBook ISBN: 978-3-030-24713-3Published: 14 August 2019

  • Series ISSN: 2196-548X

  • Series E-ISSN: 2196-5498

  • Edition Number: 1

  • Number of Pages: XI, 94

  • Number of Illustrations: 12 b/w illustrations, 5 illustrations in colour

  • Topics: Machine Learning, Pattern Recognition

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