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Advances in Knowledge Discovery and Data Mining [electronic resource] : 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part I / edited by Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin, Yang-Sae Moon.

Contributor(s): Kim, Jinho [editor.] | Shim, Kyuseok [editor.] | Cao, Longbing [editor.] | Lee, Jae-Gil [editor.] | Lin, Xuemin [editor.] | Moon, Yang-Sae [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Artificial Intelligence: 10234Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XXXII, 841 p. 242 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319574547.Subject(s): Data mining | Artificial intelligence | Information storage and retrieval systems | Application software | Database management | Data protection | Data Mining and Knowledge Discovery | Artificial Intelligence | Information Storage and Retrieval | Computer and Information Systems Applications | Database Management | Data and Information SecurityAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.312 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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.
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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.

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.

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