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Broad learning through fusionsan application on social networks /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Broad learning through fusionsby Jiawei Zhang, Philip S. Yu.
Reminder of title:	an application on social networks /
Author:	Zhang, Jiawei.
other author:	Yu, Philip S.
Published:	Cham :Springer International Publishing :2019.
Description:	xv, 419 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Data mining.
Online resource:	https://doi.org/10.1007/978-3-030-12528-8
ISBN:	9783030125288$q(electronic bk.)

Broad learning through fusionsan application on social networks /
Zhang, Jiawei.

Broad learning through fusionsan application on social networks /[electronic resource] :by Jiawei Zhang, Philip S. Yu. - Cham :Springer International Publishing :2019. - xv, 419 p. :ill., digital ;24 cm.

1 Broad Learning Introduction -- 2 Machine Learning Overview -- 3 Social Network Overview -- 4 Supervised Network Alignment -- 5 Unsupervised Network Alignment -- 6 Semi-supervised Network Alignment -- 7 Link Prediction -- 8 Community Detection -- 9 Information Diffusion -- 10 Viral Marketing -- 11 Network Embedding -- 12 Frontier and Future Directions -- References.

This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.

ISBN: 9783030125288$q(electronic bk.)

Standard No.: 10.1007/978-3-030-12528-8doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343 / Z43 2019

Dewey Class. No.: 006.312

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505 0 $a 1 Broad Learning Introduction -- 2 Machine Learning Overview -- 3 Social Network Overview -- 4 Supervised Network Alignment -- 5 Unsupervised Network Alignment -- 6 Semi-supervised Network Alignment -- 7 Link Prediction -- 8 Community Detection -- 9 Information Diffusion -- 10 Viral Marketing -- 11 Network Embedding -- 12 Frontier and Future Directions -- References.
520 $a This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.
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650 2 4 $a Probability and Statistics in Computer Science. $3 274053
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