Deep Learning for Social Media Data Analytics (Record no. 173525)

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001 - CONTROL NUMBER
control field 978-3-031-10869-3
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125034.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031108693
-- 978-3-031-10869-3
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-10869-3
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA345-345.5
072 #7 - SUBJECT CATEGORY CODE
Subject category code UN
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM018000
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Subject category code UN
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082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 620.00285
Edition number 23
245 10 - TITLE STATEMENT
Title Deep Learning for Social Media Data Analytics
Medium [electronic resource] /
Statement of responsibility, etc edited by Tzung-Pei Hong, Leticia Serrano-Estrada, Akrati Saxena, Anupam Biswas.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2022.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2022.
300 ## - PHYSICAL DESCRIPTION
Extent X, 299 p. 86 illus., 65 illus. in color.
Other physical details online resource.
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-- online resource
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490 1# - SERIES STATEMENT
Series statement Studies in Big Data,
International Standard Serial Number 2197-6511 ;
Volume number/sequential designation 113
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Node Classification using Deep Learning in Social Networks -- NN-LP-CF: Neural Network based Link Prediction on Social Networks using Centrality-based Features -- Deep Learning for Code-Mixed Text Mining in Social Media: A Brief Review -- Convolutional and Recurrent Neural Networks for Opinion Mining on Drug Reviews -- Text-based Sentiment Analysis using Deep Learning Techniques -- Social Sentiment Analysis Using Features based Intelligent Learning Techniques.
520 ## - SUMMARY, ETC.
Summary, etc This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics. .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Cooperating objects (Computer systems).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Big data.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social media.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Cyber-Physical Systems.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Big Data.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social Media.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Hong, Tzung-Pei.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Serrano-Estrada, Leticia.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Saxena, Akrati.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Biswas, Anupam.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031108686
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031108709
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031108716
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Studies in Big Data,
-- 2197-6511 ;
Volume number/sequential designation 113
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-10869-3">https://doi.org/10.1007/978-3-031-10869-3</a>
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Koha item type eBooks-CSE-Springer

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