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Advances in Knowledge Discovery and Data Mining
Details
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
Inhalt
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.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783319575285
- Genre Information Technology
- Auflage 1st ed. 2017
- Editor Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin, Yang-Sae Moon
- Lesemotiv Verstehen
- Anzahl Seiten 857
- Größe H49mm x B156mm x T234mm
- Jahr 2017
- EAN 9783319575285
- Format Kartonierter Einband
- ISBN 978-3-319-57528-5
- Titel Advances in Knowledge Discovery and Data Mining
- Untertitel 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part II
- Gewicht 1341g
- Herausgeber Springer
- Sprache Englisch