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

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, 11871

Information Systems and Applications, incl. Internet/Web, and HCI ; 11871

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 (XXII, 554 pages) : 213 illustrations, 141 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:

Orchids Classification Using Spatial Transformer Network with Adaptive Scaling

Scalable Dictionary Classifiers for Time Series Classification

Optimization of the numeric and categorical attribute weights in KAMILA mixed data clustering algorithm

Meaningful Data Sampling for a Faithful Local Explanation Method

Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor

Adaptive Orthogonal Characteristics of Bio-inspired Neural Networks

Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion

Modeling Data Driven Interactions on Property Graph

Adaptive Dimensionality Adjustment for Online "Principal Component Analysis"

Relevance Metric for Counterfactuals Selection in Decision Trees

Weighted Nearest Centroid Neighbourhood

The Prevalence of Errors in Machine Learning Experiments

A Hybrid Model for Fraud Detection on Purchase Orders

Users Intention based on Twitter Features using Text Analytics

Mixing hetero- and homogeneous models in weighted ensembles

A Hybrid Approach to Time Series Classification with Shapelets

An Ensemble Algorithm Based on Deep Learning for Tuberculosis Classification

A Data-driven Approach to Automatic Extraction of Professional Figure Profiles from Résumés

Retrieving and Processing Information from Clinical Algorithm via Formal Concept Analysis

Comparative Analysis of Approaches to Building Medical Dialog Systems in Russian

Tracking Position and Status of Electric Control Switches Based on YOLO Detector

A Self-Generating Prototype method based on Information Entropy used for Condensing Data in Classification Tasks

Transfer Knowledge between Sub-regions for Traffic Prediction using Deep Learning Method

Global Q-Learning Approach for Power Allocation in Femtocell Networks

Deep learning and Sensor Fusion Methods for Studying Gait Changes under Cognitive Load in Males and Females

Towards a robotic personal trainer for the elderly

Image Quality Constrained GAN for Super-Resolution

Use Case Prediction using Product Reviews Text Classification

Convolutional Neural Network for Core Sections Identification in Scientific Research Publications

Knowledge Inference Through Analysis of Human Activities

Representation Learning of Knowledge Graphs with Multi-scale Capsule Network

CNNPSP: Pseudouridine Sites Prediction Based on Deep Learning

A Multimodal Approach to Image Sentiment Analysis

Joining Items Clustering and Users Clustering for Evidential Collaborative Filtering

Conditioned Generative Model via Latent Semantic Controlling for Learning Deep Representation of Data

Toward A Framework for Seasonal Time Series Forecasting Using Clustering

An Evidential Imprecise Answer Aggregation Approach based on Worker Clustering

Combining Machine Learning and Classical Optimization Techniques in Vehicle to Vehicle Communication Network

Adversarial Edit Attacks for Tree Data

Non-stationary Noise Cancellation Using Deep Autoencoder based on Adversarial Learning

A Deep Learning-based Surface Defect Inspection System for Smartphone Glass

Superlinear Speedup of Parallel Population-based Metaheuristics: A Microservices and Container Virtualization Approach

Active Dataset Generation for Meta-Learning System Quality Improvement

Do You Really Follow Them? Automatic Detection of Credulous Twitter Users

User Localization Based on Call Detail Record

Automatic Ground Truth Dataset Creation for Fake News Detection in Social Media

Artificial Flora Optimization Algorithm for Task Scheduling in Cloud Computing Environment

A Significantly Faster Elastic-Ensemble for Time-Series Classification

ALIME: Autoencoder Based Approach for Local Interpretability

Detection of Abnormal Load Consumption in the Power Grid Using Clustering and Statistical Analysis

Deep Convolutional Neural Networks Based on Image Data Augmentation for Visual Object Recognition

An Efficient Scheme for Prototyping kNN in the Context of Real-Time Human Activity Recognition

A Novel Recommendation System for Next Feature in Software

Meta-learning Based Evolutionary Clustering Algorithm

Fast tree-based classification via homogeneous clustering

Ordinal equivalence classes for parallel coordinates

New Internal Clustering Evaluation Index Based on Line Segments

Threat Identification in Humanitarian Demining using Machine Learning and Spectroscopic Metal Detection.

Other Format:

Printed edition:

ISBN:

978-3-030-33607-3

9783030336073

Access Restriction:

Restricted for use by site license.