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Advances in Knowledge Discovery and ...
~
Ng, See-Kiong.
Advances in Knowledge Discovery and Data Mining = 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Advances in Knowledge Discovery and Data Mining/ edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan.
Reminder of title:
24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II /
other author:
Lauw, Hady W.
Description:
XXXVIII, 924 p. 503 illus., 242 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Artificial intelligence. -
Online resource:
https://doi.org/10.1007/978-3-030-47436-2
ISBN:
9783030474362
Advances in Knowledge Discovery and Data Mining = 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II /
Advances in Knowledge Discovery and Data Mining
24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II /[electronic resource] :edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan. - 1st ed. 2020. - XXXVIII, 924 p. 503 illus., 242 illus. in color.online resource. - Lecture Notes in Artificial Intelligence ;12085. - Lecture Notes in Artificial Intelligence ;9285.
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.
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.
ISBN: 9783030474362
Standard No.: 10.1007/978-3-030-47436-2doiSubjects--Topical Terms:
559380
Artificial intelligence.
LC Class. No.: Q334-342
Dewey Class. No.: 006.3
Advances in Knowledge Discovery and Data Mining = 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II /
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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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