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Machine Learning and Knowledge Extraction : Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26-29, 2019, Proceedings / edited by Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 11713
- Information Systems and Applications, incl. Internet/Web, and HCI ; 11713
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Database management.
- Data mining.
- User interfaces (Computer systems).
- Human-computer interaction.
- Computer arithmetic and logic units.
- Data protection.
- Artificial Intelligence.
- Database Management.
- Data Mining and Knowledge Discovery.
- User Interfaces and Human Computer Interaction.
- Arithmetic and Logic Structures.
- Data and Information Security.
- Local Subjects:
- Artificial Intelligence.
- Database Management.
- Data Mining and Knowledge Discovery.
- User Interfaces and Human Computer Interaction.
- Arithmetic and Logic Structures.
- Data and Information Security.
- Physical Description:
- 1 online resource (XIII, 416 pages) : 138 illustrations, 98 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 book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.
- Contents:
- KANDINSKY Patterns as IQ-Test for machine learning
- Machine Learning Explainability Through Comprehensible Decision Trees
- New Frontiers in Explainable AI: Understanding the GI to Interpret the GO
- Automated Machine Learning for Studying the Trade-off Between Predictive Accuracy and Interpretability
- Estimating the Driver Status Using Long Short Term Memory
- Using Relational Concept Networks for Explainable Decision Support
- Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking
- Detection of Diabetic Retinopathy and Maculopathy in Eye Fundus Images Using Deep Learning and Image Augmentation
- Semi-automated Quality Assurance for Domain-expert-driven Data Exploration - An Application to Principal Component Analysis
- Ranked MSD: A New Feature Ranking and Feature Selection Approach for Biomarker Identification
- How to improve the adaptation phase of the CBR in the medical domain
- Machine Learning for Family Doctors: A Case of Cluster Analysis for studying Aging Associated Comorbidities and Frailty
- Knowledge Extraction for Cryptographic Algorithm Validation Test Vectors by Means of Combinatorial Coverage Measurement
- An Evaluation on Robustness and Utility of Fingerprinting Schemes
- Differentially Private Obfuscation of Facial Images
- Insights into Learning Competence through Probabilistic Graphical Models
- Sparse Nerves in Practice
- Backdoor Attacks in Neural Networks - a Systematic Evaluation on Multiple Traffic Sign Datasets
- Deep Learning for Proteomics Data for Feature Selection and Classification
- Package and Classify Wireless Product Features to Their Sales Items and Categories Automatically
- Temporal diagnosis of discrete-event systems with dual knowledge Compilation
- A Case for Guided Machine Learning
- Using Ontologies to Express Prior Knowledge for Genetic Programming
- Real Time Hand Movement Trajectory Tracking for Enhancing Dementia Screening in Ageing Deaf Signers of British Sign Language
- Commonsense Reasoning using Theorem Proving and Machine Learning
- Deep structured semantic model for recommendations with heterogeneous side information in e-commerce.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-29726-8
- 9783030297268
- Access Restriction:
- Restricted for use by site license.
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