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03362nmm a2200421 u 4500 |
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EBX01000000000000001060488 |
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00000000000000.0 |
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200604 ||| eng |
| 020 |
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|a 9783030474263
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| 100 |
1 |
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|a Lauw, Hady W.
|e [editor]
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| 245 |
0 |
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|a Advances in Knowledge Discovery and Data Mining
|h Elektronische Ressource
|b 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part I
|c edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan
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| 250 |
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|a 1st ed. 2020
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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| 300 |
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|a XXXVII, 886 p. 293 illus., 207 illus. in color
|b online resource
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| 505 |
0 |
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|a Recommender Systems -- Classification -- Clustering -- Mining Social Networks -- Representation Learning and Embedding -- Mining Behavioral Data -- Deep Learning -- Feature Extraction and Selection -- Human, Domain, Organizational and Social Factors in Data Mining
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| 653 |
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|a Computer Communication Networks
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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 Artificial Intelligence
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| 653 |
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|a Computers
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| 653 |
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|a Application software
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| 653 |
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|a Computer networks
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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 Computer and Information Systems Applications
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| 653 |
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|a Computing Milieux
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| 700 |
1 |
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|a Wong, Raymond Chi-Wing
|e [editor]
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| 700 |
1 |
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|a Ntoulas, Alexandros
|e [editor]
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| 700 |
1 |
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|a Lim, Ee-Peng
|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 10.1007/978-3-030-47426-3
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-47426-3?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 two-volume set LNAI 12084 and 12085 constitutes the thoroughly refereed proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19 pandemic. The 135 full papers presented were carefully reviewed and selected from 628 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: recommender systems; classification; clustering; mining social networks; representation learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing
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