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210901 ||| eng |
| 020 |
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|a 9783030840600
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| 100 |
1 |
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|a Holzinger, Andreas
|e [editor]
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| 245 |
0 |
0 |
|a Machine Learning and Knowledge Extraction
|h Elektronische Ressource
|b 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, Virtual Event, August 17–20, 2021, Proceedings
|c edited by Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl
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| 250 |
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|a 1st ed. 2021
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2021, 2021
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| 300 |
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|a X, 365 p. 119 illus., 96 illus. in color
|b online resource
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| 505 |
0 |
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|a Digital Transformation for Sustainable Development Goals (SDGs) - a Security, Safety and Privacy Perspective on AI -- When in Doubt, Ask: Generating Answerable and Unanswerable Questions, Unsupervised -- Self-Propagating Malware Containment via Reinforcement Learning -- Text2PyCode : Machine Translation of Natural Language Intent to Python Source Code -- Automated Short Answer Grading using Deep Learning : A Survey -- Fair and Adequate Explanations -- Mining Causal Hypotheses in Categorical Time Series by Iterating on Binary Correlations -- Active Finite Reward Automaton Inference and Reinforcement Learning Using Queries and Counterexamples -- Rice seed image-to-image translation using Generative Adversarial Networks to improve weedy rice image classification -- Reliable AI through SVDD and rule extraction -- Airbnb Price Prediction Using Machine Learning and Sentiment Analysis -- Towards Financial Sentiment Analysis in a South African Landscape -- Decisions are not all equal. Introducing a utility metric based on the case-wise raters' perceptions -- Deep Convolutional Neural Network(CNN) design for pathology detection of COVID-19 in chest X-Ray Images -- Anomaly detection for skin lesion images using replicator neural networks -- On the overlap between Grad-CAM saliency maps and explainable visual features in skin cancer images -- From Explainable to Reliable Artificial Intelligence -- Explanatory Pluralism in Explainable AI -- On the Trustworthiness of Tree Ensemble Explainability Methods -- Human-in-the-loop model explanation via verbatim boundary identification in generated neighborhoods -- MAIRE - A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers -- Transparent Ensembles for Covid-19 Prognosis
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| 653 |
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|a Education / Data processing
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Database Management
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| 653 |
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|a Computers and Education
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| 653 |
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|a Data mining
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Data Mining and Knowledge Discovery
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| 653 |
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|a Database management
|
| 700 |
1 |
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|a Kieseberg, Peter
|e [editor]
|
| 700 |
1 |
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|a Tjoa, A Min
|e [editor]
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| 700 |
1 |
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|a Weippl, Edgar
|e [editor]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Information Systems and Applications, incl. Internet/Web, and HCI
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| 028 |
5 |
0 |
|a 10.1007/978-3-030-84060-0
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-84060-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 006.3
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| 520 |
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|a This book constitutes the refereed proceedings of the 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, held in virtually in August 2021. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 48 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
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