| Description |
1 online resource |
| Series |
Unsupervised and semi-supervised learning, 2522-8498 |
|
Unsupervised and semi-supervised learning.
|
| Contents |
Introduction -- Clustering large scale data -- Clustering heterogeneous data -- Distributed clustering methods -- Clustering structured and unstructured data -- Clustering and unsupervised learning for deep learning -- Deep learning methods for clustering -- Clustering high speed cloud, grid, and streaming data -- Extension of partitioning, model based, density based, grid based, fuzzy and evolutionary clustering methods for big data analysis -- Large documents and textual data clustering -- Applications of big data clustering methods -- Clustering multimedia and multi-structured data -- Large-scale recommendation systems and social media systems -- Clustering multimedia and multi-structured data -- Real life applications of big data clustering -- Validation measures for big data clustering methods -- Conclusion |
| Summary |
This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Online resource; title from PDF title page (EBSCO, viewed November 1, 2018) |
| In |
Springer eBooks |
| Subject |
Big data.
|
|
Cluster analysis.
|
|
Data mining.
|
|
Telecommunication.
|
|
Engineering.
|
|
Data Mining
|
|
Telecommunications
|
|
Engineering
|
|
telecommunications.
|
|
engineering.
|
|
Artificial intelligence.
|
|
Data mining.
|
|
Business mathematics & systems.
|
|
Pattern recognition.
|
|
Communications engineering -- telecommunications.
|
|
COMPUTERS -- Data Processing.
|
|
Big data
|
|
Cluster analysis
|
|
Data mining
|
| Form |
Electronic book
|
| Author |
Nasraoui, Olfa, 1968- editor.
|
|
Ben N'Cir, Chiheb-Eddine, editor.
|
| ISBN |
9783319978642 |
|
3319978640 |
|
9783319978659 |
|
3319978659 |
|
