Advances in Data Mining. Applications and Theoretical Aspects - 18th Industrial Conference, ICDM 2018, New York, NY, USA, July 11-12, 2018, Proceedings

This volume constitutes the proceedings of the 18th Industrial Conference on Adances in Data Mining, ICDM 2018, held in New York, NY, USA, in July 2018.
The 24 regular papers presented in this book were carefully reviewed and selected from 146 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine and agriculture, and in process control, industry, and society.

Sommario

Multimedia data.- Marketing.- Medicine.- Agriculture.- Process control.- Industry.- Society.

Riassunto

This volume constitutes the proceedings of the 18th Industrial Conference on Adances in Data Mining, ICDM 2018, held in New York, NY, USA, in July 2018.
The 24 regular papers presented in this book were carefully reviewed and selected from 146 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine and agriculture, and in process control, industry, and society.

Dettagli sul prodotto

• Con la collaborazione di: Petr Perner (Editore), Petra Perner (Editore)
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 01.01.2018
• EAN: 9783319957852
• ISBN: 978-3-31-995785-2
• Pagine: 326
• Dimensioni: 156 mm x 237 mm x 20 mm
• Peso: 511 g
• Illustrazioni: X, 326 p. 130 illus.
• Serie: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Categorie: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica; C, Data Mining, Wissensbasierte Systeme, Expertensysteme, Classification, computer science, clustering, Data Mining and Knowledge Discovery, Expert systems / knowledge-based systems, graph mining, feature selection, Time Series Mining, Forensic Data Analysis, Process Minnig, Data Mining in Marketing, Image Mining