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Advances in Knowledge Discovery and Data Mining: Lecture Notes in Computer Science, cartea 10234

Editat de Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin, Yang-Sae Moon
en Limba Engleză Paperback – 23 apr 2017
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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Specificații

ISBN-13: 9783319574530
ISBN-10: 3319574531
Pagini: 876
Ilustrații: XXXII, 841 p. 242 illus.
Dimensiuni: 155 x 235 x 47 mm
Greutate: 1.3 kg
Ediția:1st edition 2017
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

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.

Caracteristici

Includes supplementary material: sn.pub/extras Includes supplementary material: sn.pub/extras