大葉大學圖書館 |

Images in social media :categorization and organization of images and their collections /

レコード種別:	コンピュータ・メディア : 単行資料
[NT 15000414] null:	025.067
タイトル / 著者:	Images in social media : : categorization and organization of images and their collections // Susanne �rnager and Haakon Lund.
著者:	�rnager, Susanne,
その他の著者:	Lund, Haakon,
出版された:	[San Rafael, California] : : Morgan & Claypool,, 2018.
記述:	1 PDF (xviii, 101 pages) : : illustrations.
注記:	Part of: Synthesis digital library of engineering and computer science.
主題:	Pictures - Computer network resources.
主題:	Digital images - Computer network resources.
主題:	Internet research.
主題:	Eye tracking.
国際標準図書番号 (ISBN) :	9781681730806
[NT 15000227] null:	Includes bibliographical references (pages 85-100).
[NT 15000228] null:	1. Introduction and iconic language for images -- 1.1 Iconic language for images -- 1.2 The meaning of an image -- 1.3 The Shatford/Panofsky matrix --
[NT 15000229] null:	This book focuses on the methodologies, organization, and communication of digital image collection research that utilizes social media content. ("Image" is here understood as a cultural, conventional, and commercial--stock photo--representation.) The lecture offers expert views that provide different interpretations of images and their potential implementations. Linguistic and semiotic methodologies as well as eye-tracking research are employed to both analyze images and comprehend how humans consider them, including which salient features generally attract viewers' attention. This literature review covers image--specifically photographic--research since 2005, when major social media platforms emerged. A citation analysis includes an overview of co-citation maps that demonstrate the nexus of image research literature and the journals in which they appear. Eye tracking tests whether scholarly templates focus on the proper features of an image, such as people, objects, time, etc., and if a prescribed theme affects the eye movements of the observer. The results may point to renewed requirements for building image search engines. As it stands, image management already requires new algorithms and a new understanding that involves text recognition and very large database processing. The aim of this book is to present different image research areas and demonstrate the challenges image research faces. The book's scope is, by necessity, far from comprehensive, since the field of digital image research does not cover fake news, image manipulation, mobile photos, etc.; these issues are very complex and need a publication of their own. This book should primarily be useful for students in library and information science, psychology, and computer science.
電子資源:	http://ieeexplore.ieee.org/servlet/opac?bknumber=8290768

Images in social media :categorization and organization of images and their collections /
�rnager, Susanne,

Images in social media :categorization and organization of images and their collections /Susanne �rnager and Haakon Lund. - [San Rafael, California] :Morgan & Claypool,2018. - 1 PDF (xviii, 101 pages) :illustrations. - Synthesis lectures on information concepts, retrieval, and services,# 621947-9468 ;. - Synthesis digital library of engineering and computer science..

Part of: Synthesis digital library of engineering and computer science.

Includes bibliographical references (pages 85-100).

1. Introduction and iconic language for images -- 1.1 Iconic language for images -- 1.2 The meaning of an image -- 1.3 The Shatford/Panofsky matrix --

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

Compendex

This book focuses on the methodologies, organization, and communication of digital image collection research that utilizes social media content. ("Image" is here understood as a cultural, conventional, and commercial--stock photo--representation.) The lecture offers expert views that provide different interpretations of images and their potential implementations. Linguistic and semiotic methodologies as well as eye-tracking research are employed to both analyze images and comprehend how humans consider them, including which salient features generally attract viewers' attention. This literature review covers image--specifically photographic--research since 2005, when major social media platforms emerged. A citation analysis includes an overview of co-citation maps that demonstrate the nexus of image research literature and the journals in which they appear. Eye tracking tests whether scholarly templates focus on the proper features of an image, such as people, objects, time, etc., and if a prescribed theme affects the eye movements of the observer. The results may point to renewed requirements for building image search engines. As it stands, image management already requires new algorithms and a new understanding that involves text recognition and very large database processing. The aim of this book is to present different image research areas and demonstrate the challenges image research faces. The book's scope is, by necessity, far from comprehensive, since the field of digital image research does not cover fake news, image manipulation, mobile photos, etc.; these issues are very complex and need a publication of their own. This book should primarily be useful for students in library and information science, psychology, and computer science.

Mode of access: World Wide Web.

ISBN: 9781681730806

Standard No.: 10.2200/S00821ED1V01Y201712ICR062doiSubjects--Topical Terms:

729061
Pictures
--Computer network resources.Subjects--Index Terms:

imagesIndex Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: N59 / .O753 2018

Dewey Class. No.: 025.067

Images in social media :categorization and organization of images and their collections /
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505 8 $a 2. Literature review: state of the art -- 2.1 Prisma methodology -- 2.2 Bibliometric networks between the analyzed documents -- 2.3 Analyzing the research papers with grounded theory -- 2.4 Category domains -- 2.4.1 Historic photos -- 2.4.2 Journalistic photographs -- 2.4.3 Photos used in various professions -- 2.5 Category indexing -- 2.5.1 Collection description -- 2.5.2 Metadata -- 2.5.3 Sub-category guidelines -- 2.5.4 Sub-category emotions -- 2.6 Category retrieval -- 2.6.1 Sub-category framework -- 2.6.2 CBIR -- 2.6.3 Sub-category queries -- 2.6.4 Sub-category (query) taxonomy -- 2.6.5 User needs -- 2.7 Summary --
505 8 $a 3. Natural scene perception and eye tracking -- 3.1 The technology behind recording eye movements -- 3.2 Eye movement research -- 3.2.1 Research in visual search -- 3.2.2 Research in reading -- 3.2.3 Application of eye tracking in usability studies -- 3.2.4 Natural scene perception -- 3.2.5 Measurements in eye movements -- 3.2.6 Recent developments -- 3.3 Experiment -- 3.3.1 Methodology -- 3.3.2 Analysis of assigned tags --
505 8 $a 4. Trends in handling future image collections -- Bibliography -- Authors' biographies.
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510 0 $a Compendex
510 0 $a INSPEC
510 0 $a Google scholar
510 0 $a Google book search
520 3 $a This book focuses on the methodologies, organization, and communication of digital image collection research that utilizes social media content. ("Image" is here understood as a cultural, conventional, and commercial--stock photo--representation.) The lecture offers expert views that provide different interpretations of images and their potential implementations. Linguistic and semiotic methodologies as well as eye-tracking research are employed to both analyze images and comprehend how humans consider them, including which salient features generally attract viewers' attention. This literature review covers image--specifically photographic--research since 2005, when major social media platforms emerged. A citation analysis includes an overview of co-citation maps that demonstrate the nexus of image research literature and the journals in which they appear. Eye tracking tests whether scholarly templates focus on the proper features of an image, such as people, objects, time, etc., and if a prescribed theme affects the eye movements of the observer. The results may point to renewed requirements for building image search engines. As it stands, image management already requires new algorithms and a new understanding that involves text recognition and very large database processing. The aim of this book is to present different image research areas and demonstrate the challenges image research faces. The book's scope is, by necessity, far from comprehensive, since the field of digital image research does not cover fake news, image manipulation, mobile photos, etc.; these issues are very complex and need a publication of their own. This book should primarily be useful for students in library and information science, psychology, and computer science.
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