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Semantic Hyper/Multimedia Adaptation

Overview of attention for book
Cover of 'Semantic Hyper/Multimedia Adaptation'

Table of Contents

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    Book Overview
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    Chapter 1 An Individual Differences Approach in Designing Ontologies for Efficient Personalization
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    Chapter 2 Formal Methods in High-Level and System Synthesis
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    Chapter 3 Vision Based Semantic Analysis of Surveillance Videos
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    Chapter 4 On the Use of Semantic Technologies to Support Education, Mobility and Employability
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    Chapter 5 Recommendation Systems: Bridging Technical Aspects with Marketing Implications
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    Chapter 6 Exploring New Ways for Personalized E-Commerce through Digital TV
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    Chapter 7 Towards Automated Navigation over Multilingual Content
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    Chapter 8 Personalized and Adaptive Access to Services – The Semantic Web Services Approach
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    Chapter 9 “With a Little Help from My Friends”: Context Aware Help and Guidance Using the Social Network
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    Chapter 10 Influential Users in Social Networks
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    Chapter 11 A Client-Side Privacy Framework for Web Personalization
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    Chapter 12 Semantic Hyper/Multimedia Adaptation
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    Chapter 13 Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 and MPEG-21 Standards
Attention for Chapter 13: Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 and MPEG-21 Standards
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Citations

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Chapter title
Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 and MPEG-21 Standards
Chapter number 13
Book title
Semantic Hyper/Multimedia Adaptation
Published by
Springer Berlin Heidelberg, January 2013
DOI 10.1007/978-3-642-28977-4_13
Book ISBNs
978-3-64-228976-7, 978-3-64-228977-4
Authors

Emmanouil Skondras, Angelos Michalas, Malamati Louta, George Kouzas

Editors

Ioannis E. Anagnostopoulos, Mária Bieliková, Phivos Mylonas, Nicolas Tsapatsoulis

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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