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Intelligent Data Engineering and Automated Learning - IDEAL 2019 : 20th International Conference, Manchester, UK, November 14-16, 2019, Proceedings, Part II / edited by Hujun Yin, David Camacho, Peter Tino, Antonio J. Tallón-Ballesteros, Ronaldo Menezes, Richard Allmendinger.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Yin, Hujun., Editor.
Camacho, David, Editor.
Tino, Peter, Editor.
Tallón-Ballesteros, Antonio J., Editor.
Menezes, Ronaldo., Editor.
Allmendinger, Richard., Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 11872
Information Systems and Applications, incl. Internet/Web, and HCI ; 11872
Language:
English
Subjects (All):
Data mining.
Education-Data processing.
Computer science.
Application software.
Computer engineering.
Computer networks.
Artificial intelligence.
Data Mining and Knowledge Discovery.
Computers and Education.
Theory of Computation.
Computer and Information Systems Applications.
Computer Engineering and Networks.
Artificial Intelligence.
Local Subjects:
Data Mining and Knowledge Discovery.
Computers and Education.
Theory of Computation.
Computer and Information Systems Applications.
Computer Engineering and Networks.
Artificial Intelligence.
Physical Description:
1 online resource (XXI, 364 pages) : 115 illustrations, 86 illustrations in color.
Edition:
1st ed. 2019.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2019.
System Details:
text file PDF
Summary:
This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI.
Contents:
Special Session on Fuzzy Systems and Intelligent Data Analysis
Computational Generalization in Taxonomies Applied to: (1) Analyze Tendencies of Research and (2) Extend User Audiences
Unsupervised Initialization of Archetypal Analysis and Proportional Membership Fuzzy Clustering
Special Session on Machine Learning towards Smarter Multimodal Systems
Multimodal Web Based Video Annotator with Real-Time Human Pose Estimation
New Interfaces for Classifying Performance Gestures in Music
Special Session on Data Selection in Machine Learning
Classifying Ransomware Using Machine Learning Algorithms
Artificial Neural Networks in Mathematical Mini-Games for Automatic Students Learning Styles Identification: A First Approach
The Use of Unified Activity Records to Predict Requests Made by Applications for External Services
Fuzzy Clustering Approach to Data Selection for Computer Usage in Headache Disorders
Multitemporal Aerial Image Registration Using Semantic Features
Special Session on Machine Learning in Healthcare
Brain Tumor Classification Using Principal Component Analysis and Kernel Support Vector Machine
Modelling survival by machine learning methods in liver transplantation: application to the UNOS dataset
Design and Development of an Automatic Blood Detection System for Capsule Endoscopy Images
Comparative Analysis for Computer-Based Decision Support: Case Study of Knee Osteoarthritis
A Clustering-Based Patient Grouper for Burn Care
A comparative assessment of Feed-Forward and Convolutional Neural Networks for the classification of prostate lesions
Special Session on Machine Learning in Automatic Control
A Method based on Filter Bank Common Spatial Pattern for Multiclass Motor Imagery BCI
Safe Deep Neural Network-driven Autonomous Vehicles Using Software Safety Cages
Wave and viscous resistance estimation by NN
Neural controller of UAVs with inertia variations
Special Session on Finance and Data Mining
A Metric Framework for quantifying Data Concentration
Adaptive Machine Learning-Based Stock Prediction using Financial Time Series Technical Indicators
Special Session on Knowledge Discovery from Data
Exploiting Online Newspaper Articles Metadata for Profiling City Areas
Modelling the Social Interactions in Ant Colony Optimization
An Innovative Deep-Learning Algorithm for Supporting the Approximate Classication of Workloads in Big Data Environments
Control-flow Business Process Summarization via Activity Contraction
Classifying Flies Based on Reconstructed Audio Signals
Studying the Evolution of the 'Circular Economy' Concept using Topic Modelling
Mining Frequent Distributions in Time Series
Time Series Display for Knowledge Discovery on Selective Laser Melting Machines
Special Session on Machine Learning Algorithms for Hard Problems
Using Prior Knowledge to Facilitate Computational Reading of Arabic Calligraphy
SMOTE Algorithm Variations in Balancing Data Streams
Multi-Class Text Complexity Evaluation via Deep Neural Networks
Imbalance reduction techniques applied to ECG classification problem
Machine Learning Methods for Fake News Classification
A genetic-based ensemble learning applied to imbalanced data classification
The feasibility of deep learning use for adversarial model extraction in the cybersecurity domain.
Other Format:
Printed edition:
ISBN:
978-3-030-33617-2
9783030336172
Access Restriction:
Restricted for use by site license.

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