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Advances in knowledge discovery and ...
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Pacific-Asia Conference on Knowledge Discovery and Data Mining (2019 :)
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Advances in knowledge discovery and data mining = 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019 : proceedings.. Part I /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Advances in knowledge discovery and data mining/ edited by Qiang Yang ... [et al.].
Reminder of title:
23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019 : proceedings.
remainder title:
PAKDD 2019
other author:
Yang, Qiang.
corporate name:
Pacific-Asia Conference on Knowledge Discovery and Data Mining
Published:
Cham :Springer International Publishing : : 2019.,
Description:
xl, 627 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Data mining - Congresses. -
Online resource:
https://doi.org/10.1007/978-3-030-16148-4
ISBN:
9783030161484
Advances in knowledge discovery and data mining = 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019 : proceedings.. Part I /
Advances in knowledge discovery and data mining
23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019 : proceedings.Part I /[electronic resource] :PAKDD 2019edited by Qiang Yang ... [et al.]. - Cham :Springer International Publishing :2019. - xl, 627 p. :ill., digital ;24 cm. - Lecture notes in computer science,114390302-9743 ;. - Lecture notes in computer science ;11439..
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 feature selection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.
ISBN: 9783030161484
Standard No.: 10.1007/978-3-030-16148-4doiSubjects--Topical Terms:
551626
Data mining
--Congresses.
LC Class. No.: QA76.9.D343
Dewey Class. No.: 006.312
Advances in knowledge discovery and data mining = 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019 : proceedings.. Part I /
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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 feature selection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.
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Computer Science (Springer-11645)
based on 0 review(s)
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Attachments
W9370212
電子資源
11.線上閱覽_V
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EB QA76.9.D343
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