TY  - BOOK
AU  - Lauw,Hady W.
AU  - Wong,Raymond Chi-Wing
AU  - Ntoulas,Alexandros
AU  - Lim,Ee-Peng
AU  - Ng,See-Kiong
AU  - Pan,Sinno Jialin
ED  - SpringerLink (Online service)
TI  - Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part I 
T2  - Lecture Notes in Artificial Intelligence,
SN  - 9783030474263
AV  - Q334-342 
PY  - 2020///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Artificial intelligence
KW  - Computer networks 
KW  - Application software
KW  - Computers
KW  - Image processing
KW  - Digital techniques
KW  - Computer vision
KW  - Artificial Intelligence
KW  - Computer Communication Networks
KW  - Computer and Information Systems Applications
KW  - Computing Milieux
KW  - Computer Imaging, Vision, Pattern Recognition and Graphics
N1  - 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
N2  - 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
UR  - https://doi.org/10.1007/978-3-030-47426-3
ER  -