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

by Jinho Kim (Editor), Kyuseok Shim (Editor), Longbing Cao (Editor), Jae-Gil Lee (Editor), Xuemin Lin (Editor)

Overview

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.

Product Details

ISBN-13:	9783319574547
Publisher:	Springer-Verlag New York, LLC
Publication date:	04/25/2017
Series:	Lecture Notes in Computer Science , #10234
Sold by:	Barnes & Noble
Format:	eBook
File size:	17 MB
Note:	This product may take a few minutes to download.

Table of 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.