Advances in Knowledge Discovery and Data Mining
Advances in Knowledge Discovery and Data Mining
Buch
- 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11¿14, 2020, Proceedings, Part I
- Herausgeber: Hady W. Lauw, Raymond Chi-Wing Wong, Sinno Jialin Pan, Ee-Peng Lim, See-Kiong Ng, Alexandros Ntoulas
lieferbar innerhalb 2-3 Wochen
(soweit verfügbar beim Lieferanten)
(soweit verfügbar beim Lieferanten)
EUR 116,09**
EUR 109,51*
- Springer International Publishing AG, 05/2020
- Einband: Kartoniert / Broschiert, Paperback
- Sprache: Englisch
- ISBN-13: 9783030474256
- Bestellnummer: 10110240
- Umfang: 924 Seiten
- Nummer der Auflage: 20001
- Auflage: 1st ed. 2020
- Gewicht: 1369 g
- Maße: 235 x 155 mm
- Stärke: 49 mm
- Erscheinungstermin: 9.5.2020
- Serie: Lecture Notes in Artificial Intelligence - Band 12084
Achtung: Artikel ist nicht in deutscher Sprache!
Weitere Ausgaben von Advances in Knowledge Discovery and Data Mining
Klappentext
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.