ENGLISH

Advances in Knowledge Discovery and Data Mining: 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part I

By Xuemin Lin , Longbing Cao , Kyuseok Shim , Jinho Kim , Jae-Gil Lee , Yang-Sae Moon (eds.)

Book information

Publisher
Springer International Publishing
Year
2017
ISBN
978-3-319-57453-0, 978-3-319-57454-7
DOI
10.1007/978-3-319-57454-7
Language
english
Format
PDF
Filesize
45 MB (47137813 bytes)
Series
Lecture Notes in Computer Science 10234
Edition
1
Pages
XXXII, 841\866
Time added
2017-06-25 01:09:08
Data Mining and Knowledge Discovery;Artificial Int

Description

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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