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Intelligent Data Engineering and Automated Learning – IDEAL 2019 = 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Intelligent Data Engineering and Automated Learning – IDEAL 2019/ edited by Hujun Yin, David Camacho, Peter Tino, Antonio J. Tallón-Ballesteros, Ronaldo Menezes, Richard Allmendinger.
其他題名:	20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I /
其他作者:	Yin, Hujun.
面頁冊數:	XXII, 554 p. 213 illus., 141 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Data mining. -
電子資源:	https://doi.org/10.1007/978-3-030-33607-3
ISBN:	9783030336073

Intelligent Data Engineering and Automated Learning – IDEAL 2019 = 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I /
Intelligent Data Engineering and Automated Learning – IDEAL 201920th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I /[electronic resource] :edited by Hujun Yin, David Camacho, Peter Tino, Antonio J. Tallón-Ballesteros, Ronaldo Menezes, Richard Allmendinger. - 1st ed. 2019. - XXII, 554 p. 213 illus., 141 illus. in color.online resource. - Information Systems and Applications, incl. Internet/Web, and HCI ;11871. - Information Systems and Applications, incl. Internet/Web, and HCI ;9149.

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.

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.

ISBN: 9783030336073

Standard No.: 10.1007/978-3-030-33607-3doiSubjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Intelligent Data Engineering and Automated Learning – IDEAL 2019 = 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I /
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