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Big Data, Machine Learning, and Applications
Details
This book constitutes refereed proceedings of the First International First International Conference on Big Data, Machine Learning, and Applications, BigDML 2019, held in Silchar, India, in December.
The 6 full papers and 3 short papers were carefully reviewed and selected from 152 submissions. The papers present research on such topics as computing methodology; machine learning; artificial intelligence; information systems; security and privacy.
Klappentext
This book constitutes refereed proceedings of the First International First International Conference on Big Data, Machine Learning, and Applications, BigDML 2019, held in Silchar, India, in December. The 6 full papers and 3 short papers were carefully reviewed and selected from 152 submissions. The papers present research on such topics as computing methodology; machine learning; artificial intelligence; information systems; security and privacy.
Inhalt
TUKNN: A Parallel KNN Algorithm to handle large Data.- Cluster-Based Regression Model for Predicting Aqueous Solubility of the Molecules.- A Preventive intrusion Detection architecture using Adaptive Blockchain Method.- Automatic Extraction of Locations from News Articles using Domain Knowledge.- Uncovering Data Warehouse Issues & Challenges in Big Data Management.- Intrusion detection in ad hoc network using machine learning technique.- Big Data Issues in SDN based IoT: A Review.- Classification of Diffuse Lung Diseases using Heterogeneous Ensemble Classifiers.- NISAR Real Time data processing A Simple and Futuristic View.
Weitere Informationen
- Allgemeine Informationen
- Sprache Englisch
- Herausgeber Springer International Publishing
- Gewicht 189g
- Untertitel First International Conference, BigDML 2019, Silchar, India, December 16-19, 2019, Revised Selected Papers
- Titel Big Data, Machine Learning, and Applications
- Veröffentlichung 28.11.2020
- ISBN 3030626245
- Format Kartonierter Einband
- EAN 9783030626242
- Jahr 2020
- Größe H235mm x B155mm x T7mm
- Anzahl Seiten 116
- Lesemotiv Verstehen
- Editor Ripon Patgiri, Dalton Meitei Thounaojam, Malaya Dutta Borah, Sivaji Bandyopadhyay
- Auflage 1st edition 2020
- GTIN 09783030626242