Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications

Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications

Nasraoui, Olfa
Ben n'Cir, Chiheb-Eddine

Hardcover

Series: Unsupervised and Semi-Supervised Learning

Business GeneralTechnology & EngineeringDatabases

ISBN10: 3319978632
ISBN13: 9783319978635
Publisher: Springer Nature
Published: Nov 8 2018
Pages: 187
Weight: 1.01
Height: 0.50 Width: 6.14 Depth: 9.21
Language: English

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.

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