Advances in Knowledge Discovery and Data Mining 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part II /
Advances in Knowledge Discovery and Data Mining 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part II / [electronic resource] :
edited by Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin, Yang-Sae Moon.
- 1st ed. 2017.
- XXXII, 857 p. 252 illus. online resource.
- Lecture Notes in Artificial Intelligence, 10235 2945-9141 ; .
- Lecture Notes in Artificial Intelligence, 10235 .
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.
9783319575292
10.1007/978-3-319-57529-2 doi
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 Security.
QA76.9.D343
006.312
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.
9783319575292
10.1007/978-3-319-57529-2 doi
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 Security.
QA76.9.D343
006.312