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Centrality and Diversity in Search

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

  • M.N. Murty
  • Anirban Biswas
Book

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

Table of contents

  1. Front Matter
    Pages i-xi
  2. M. N. Murty, Anirban Biswas
    Pages 1-12
  3. M. N. Murty, Anirban Biswas
    Pages 13-28
  4. M. N. Murty, Anirban Biswas
    Pages 29-47
  5. M. N. Murty, Anirban Biswas
    Pages 49-63
  6. M. N. Murty, Anirban Biswas
    Pages 65-69
  7. M. N. Murty, Anirban Biswas
    Pages 71-86
  8. M. N. Murty, Anirban Biswas
    Pages 87-87
  9. Back Matter
    Pages 89-94

About this book

Introduction

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.

 

Keywords

Centrality Diversity Search Artificial Intelligence Deep Learning Machine Learning Pattern Recognition Social Networks Optimization Representation

Authors and affiliations

  • M.N. Murty
    • 1
  • Anirban Biswas
    • 2
  1. 1.Department of Computer Science and AutomationIndian Institute of ScienceBengaluruIndia
  2. 2.Department of Computer Science and AutomationIndian Institute of ScienceBengaluruIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-24713-3
  • Copyright Information The Author(s), under exclusive license to Springer Nature Switzerland AG, part of Springer Nature 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-24712-6
  • Online ISBN 978-3-030-24713-3
  • Series Print ISSN 2196-548X
  • Series Online ISSN 2196-5498
  • Buy this book on publisher's site