Clustering methods for big data analytics techniques, toolboxes and applications
Olfa Nasraoui, Chiheb-Eddine Ben N'Cir, editors (Springer Nature, 2019)
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| 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. |
 Clustering Methods for Big Data Analytics.pdf :: Unduh |
| No. Panggil : | e20507207 |
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| Penerbitan : | Switzerland: Springer Nature, 2019 |
| Sumber Pengatalogan: | LibUI eng rda |
| Tipe Konten: | text |
| Tipe Media: | computer |
| Tipe Pembawa: | online resource |
| Deskripsi Fisik: | ix, 187 pages : illustration |
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| No. Panggil | No. Barkod | Ketersediaan |
|---|---|---|
| e20507207 | 02-20-286961937 | TERSEDIA |
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| Tidak ada ulasan pada koleksi ini: 20507207 |
