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Machine Learning and Knowledge Extraction [[electronic resource] ] : 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



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Titolo: Machine Learning and Knowledge Extraction [[electronic resource] ] : 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 Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Edizione: 1st ed. 2019.
Descrizione fisica: 1 online resource (XIII, 416 p. 138 illus., 98 illus. in color.)
Disciplina: 004
Soggetto topico: Artificial intelligence
Database management
Data mining
User interfaces (Computer systems)
Arithmetic and logic units, Computer
Computer security
Artificial Intelligence
Database Management
Data Mining and Knowledge Discovery
User Interfaces and Human Computer Interaction
Arithmetic and Logic Structures
Systems and Data Security
Persona (resp. second.): HolzingerAndreas
KiesebergPeter
TjoaA Min
WeipplEdgar
Nota di contenuto: 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.
Sommario/riassunto: 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.
Titolo autorizzato: Machine Learning and Knowledge Extraction  Visualizza cluster
ISBN: 3-030-29726-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 996466439403316
Lo trovi qui: Univ. di Salerno
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Serie: Information Systems and Applications, incl. Internet/Web, and HCI ; ; 11713