Intelligent Data Engineering and Automated Learning – IDEAL 2020
21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II
Editors: Analide, C., Novais, P., Camacho, D., Yin, H. (Eds.)
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- About this book
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This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.*
The 93 papers presented were carefully reviewed and selected from 134 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 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI.
* The conference was held virtually due to the COVID-19 pandemic.
- Table of contents (60 chapters)
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A Preprocessing Approach for Class-Imbalanced Data Using SMOTE and Belief Function Theory
Pages 3-11
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Multi-agent Based Manifold Denoising
Pages 12-24
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A Novel Evaluation Metric for Synthetic Data Generation
Pages 25-34
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Data Pre-processing and Data Generation in the Student Flow Case Study
Pages 35-43
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Enhanced Credit Prediction Using Artificial Data
Pages 44-53
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Table of contents (60 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Intelligent Data Engineering and Automated Learning – IDEAL 2020
- Book Subtitle
- 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II
- Editors
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- Cesar Analide
- Paulo Novais
- David Camacho
- Hujun Yin
- Series Title
- Information Systems and Applications, incl. Internet/Web, and HCI
- Series Volume
- 12490
- Copyright
- 2020
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-62365-4
- DOI
- 10.1007/978-3-030-62365-4
- Softcover ISBN
- 978-3-030-62364-7
- Edition Number
- 1
- Number of Pages
- XXV, 624
- Number of Illustrations
- 32 b/w illustrations, 161 illustrations in colour
- Topics
