| Title | : | Clustering Methods for Big Data Analytics |
|---|---|---|
| Author | : | Olfa Nasraoui & Chiheb-Eddine Ben N'Cir |
| Release | : | 2018-10-27 |
| Kind | : | ebook |
| Genre | : | Engineering, Books, Professional & Technical, Computers & Internet, Computers, Databases, Science & Nature, Mathematics |
| Size | : | 15375091 |
| 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. |
