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000868009 019__ $$a1099773689
000868009 020__ $$a9783030161484$$q(electronic book)
000868009 020__ $$a303016148X$$q(electronic book)
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000868009 0247_ $$a10.1007/978-3-030-16148-4$$2doi
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000868009 1112_ $$aPAKDD (Conference)$$n(23rd :$$d2019 :$$cMacau, China)
000868009 24510 $$aAdvances in knowledge discovery and data mining :$$b23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings.$$nPart I /$$cQiang Yang, Zhi-Hua Zhou, Zhiguo Gong, Min-Ling Zhang, Sheng-Jun Huang (eds.).
000868009 2463_ $$aPAKDD 2019
000868009 264_1 $$aCham :$$bSpringer,$$c2019.
000868009 300__ $$a1 online resource (xl, 627 pages) :$$billustrations.
000868009 336__ $$atext$$btxt$$2rdacontent
000868009 337__ $$acomputer$$bc$$2rdamedia
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000868009 4901_ $$aLecture notes in computer science ;$$v11439
000868009 4901_ $$aLecture notes in artificial intelligence
000868009 4901_ $$aLNCS sublibrary. SL 7, Artificial intelligence
000868009 500__ $$aInternational conference proceedings.
000868009 500__ $$aIncludes author index.
000868009 506__ $$aAccess limited to authorized users.
000868009 520__ $$aThe three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and feature selection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.
000868009 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 10, 2019).
000868009 650_0 $$aData mining$$vCongresses.
000868009 7001_ $$aYang, Qiang,$$d1961-$$eeditor.
000868009 7001_ $$aZhou, Zhi-Hua$$c(Computer scientist),$$eeditor.
000868009 7001_ $$aGong, Zhiguo.,$$eeditor.
000868009 7001_ $$aZhang, Min-Ling,$$eeditor.
000868009 7001_ $$aHuang, Sheng-Jun,$$eeditor.
000868009 77608 $$iPrint version:$$z9783030161477
000868009 830_0 $$aLecture notes in computer science ;$$v11439.
000868009 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
000868009 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
000868009 852__ $$bebk
000868009 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-16148-4$$zOnline Access$$91397441.1
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