Overview
- Presents recent research on complex networks representing engineered and self-organized social systems
- Places special emphasis on the extraction, analysis and applications of software, ontology, and co-authorship networks
- Explains how metrics, models, and techniques developed in the framework of complex network theory can be applied in software engineering, ontology engineering, and scientometrics
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 148)
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Table of contents (8 chapters)
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Front Matter
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Introduction
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Front Matter
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Software and Ontology Networks: Complex Networks in Source Code
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Front Matter
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Co-authorship Networks: Social Networks of Research Collaboration
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Front Matter
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Keywords
About this book
This book provides a comprehensive review of complex networks from three different domains, presents novel methods for analyzing them, and highlights applications with accompanying case studies. Special emphasis is placed on three specific kinds of complex networks of high technological and scientific importance: software networks extracted from the source code of computer programs, ontology networks describing semantic web ontologies, and co-authorship networks reflecting collaboration in science. The book is primarily intended for researchers, teachers and students interested in complex networks and network data analysis. However, it will also be valuable for researchers dealing with software engineering, ontology engineering and scientometrics, as it demonstrates how complex network analysis can be used to address important research issues in these three disciplines.
Authors and Affiliations
Bibliographic Information
Book Title: Complex Networks in Software, Knowledge, and Social Systems
Authors: Miloš Savić, Mirjana Ivanović, Lakhmi C. Jain
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-319-91196-0
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2019
Hardcover ISBN: 978-3-319-91194-6Published: 24 May 2018
Softcover ISBN: 978-3-030-08195-9Published: 26 January 2019
eBook ISBN: 978-3-319-91196-0Published: 10 May 2018
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XX, 317
Number of Illustrations: 3 b/w illustrations, 36 illustrations in colour
Topics: Computational Intelligence, Complexity, Artificial Intelligence, Applications of Graph Theory and Complex Networks, Library Science