Centrality and Diversity in Search
Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition
Authors: Murty, M.N., Biswas, Anirban
Free Preview- 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
Buy this book
- 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.
- 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.
- Table of contents (7 chapters)
-
-
Introduction
Pages 1-12
-
Searching
Pages 13-28
-
Representation
Pages 29-47
-
Clustering and Classification
Pages 49-63
-
Ranking
Pages 65-69
-
Table of contents (7 chapters)
Recommended for you
Bibliographic Information
- 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
- Copyright
- 2019
- Publisher
- Springer International Publishing
- Copyright Holder
- The Author(s), under exclusive license to Springer Nature Switzerland AG, part of Springer Nature
- eBook ISBN
- 978-3-030-24713-3
- DOI
- 10.1007/978-3-030-24713-3
- Softcover ISBN
- 978-3-030-24712-6
- Series ISSN
- 2196-548X
- Edition Number
- 1
- Number of Pages
- XI, 94
- Number of Illustrations
- 12 b/w illustrations, 5 illustrations in colour
- Topics
*immediately available upon purchase as print book shipments may be delayed due to the COVID-19 crisis. ebook access is temporary and does not include ownership of the ebook. Only valid for books with an ebook version. Springer Reference Works and instructor copies are not included.
