Advances in Knowledge Discovery and Data Mining
21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part I
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Beschreibung
This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017.
The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.
Includes supplementary material: sn.pub/extras Includes supplementary material: sn.pub/extras
Autor*in
Jinho Kim
Themen in »Advances in Knowledge Discovery and Data Mining«
crowdsourcing recommender systems security statistical methods for data mining Web mining anomaly detection classification clustering data mining decision trees deep learning dynamic networks feature extraction genetic algorithm high performance data mining