Data mining
Se alle bogdetaljer →
Advances in Knowledge Discovery and Data Mining
23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part III
Udgivet af Springer Nature Switzerland AG
ISBN
9783030161415
Om denne bog
The three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019.The 137 full papers presented were carefully reviewed and selected from 542 submissions. The paper…
Boghandelspriser
| Boghandel | Titel | Format | ISBN | Pris | Lagerstatus | Levering | |
|---|---|---|---|---|---|---|---|
Ingen boghandelstilbud endnuVi har titlen i kataloget. Priser vises her, når boghandlere lister den. |
|||||||
5
0
4
0
3
0
2
0
1
0
0%
Anbefaler
0
Verificeret
Ingen anmeldelser endnu
Bogdetaljer
Forlag
Springer Nature Switzerland AG
Kategori
Data mining
ISBN-13
9783030161415
EAN
9783030161415
Format
Hæftet
Sprog
Engelsk
sider
556
Undertitel
- 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part III
Produktbeskrivelse
The three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019.The 137 full papers presented were carefully reviewed and selected from 542 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: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and featureselection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.
Prishistorik
Indlæser prishistorik...