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220613 ||| eng |
| 020 |
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|a 9783031059810
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| 100 |
1 |
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|a Gama, João
|e [editor]
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| 245 |
0 |
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|a Advances in Knowledge Discovery and Data Mining
|h Elektronische Ressource
|b 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022, Proceedings, Part III
|c edited by João Gama, Tianrui Li, Yang Yu, Enhong Chen, Yu Zheng, Fei Teng
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| 250 |
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|a 1st ed. 2022
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2022, 2022
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| 300 |
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|a XV, 384 p. 119 illus., 109 illus. in color
|b online resource
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| 505 |
0 |
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|a Data Science -- Big Data -- Data mining. Model selection, -- Biological data -- IoT data, -- Deep learning. Meta-learning -- Security -- Privacy
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| 653 |
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|a Image processing / Digital techniques
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| 653 |
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|a Computer vision
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| 653 |
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|a Computer Application in Social and Behavioral Sciences
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| 653 |
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|a Information Storage and Retrieval
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Social sciences / Data processing
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| 653 |
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|a Data mining
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| 653 |
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|a Application software
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| 653 |
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|a Information storage and retrieval systems
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| 653 |
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|a Computer Imaging, Vision, Pattern Recognition and Graphics
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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 Computer and Information Systems Applications
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| 700 |
1 |
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|a Li, Tianrui
|e [editor]
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| 700 |
1 |
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|a Yu, Yang
|e [editor]
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| 700 |
1 |
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|a Chen, Enhong
|e [editor]
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| 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 Lecture Notes in Artificial Intelligence
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| 028 |
5 |
0 |
|a 10.1007/978-3-031-05981-0
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-031-05981-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 006.3
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| 520 |
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|a The 3-volume set LNAI 13280, LNAI 13281 and LNAI 13282 constitutes the proceedings of the 26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2022, which was held during May 2022 in Chengdu, China. The 121 papers included in the proceedings were carefully reviewed and selected from a total of 558 submissions. They were organized in topical sections as follows: Part I: Data Science and Big Data Technologies, Part II: Foundations; and Part III: Applications
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