Learning from Data Streams in Evolving Environments: Methods and Applications

Moamar Sayed-Mouchaweh (Curatore)

Springer International Publishing AG, 2018

This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field. Provides multiple examples to facilitate the understanding data streams in non-stationary environments; Presents several application cases to show how the methods solve different real world problems; Discusses the links between methods to help stimulate new research and application directions.

• Curatore: Moamar Sayed-Mouchaweh
• Editore: Springer International Publishing AG
• Collana: Studies in Big Data
• Anno: 2018
• Rilegatura: Hardback
• Pagine: 317 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319898025

Testo in English