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Adaptive Multimedia Retrieval. Identifying, Summarizing, and Recommending Image and Music

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Cover of 'Adaptive Multimedia Retrieval. Identifying, Summarizing, and Recommending Image and Music'

Table of Contents

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    Book Overview
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    Chapter 1 The Future of Audio Reproduction
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    Chapter 2 Using Thematic Ontologies for User- and Group-Based Adaptive Personalization in Web Searching
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    Chapter 3 A Poset Based Approach for Condition Weighting
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    Chapter 4 Adaptive User Modeling for Content-Based Music Retrieval
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    Chapter 5 Towards User-Adaptive Structuring and Organization of Music Collections
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    Chapter 6 An Approach to Automatically Tracking Music Preference on Mobile Players
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    Chapter 7 Music Thumbnailing Incorporating Harmony- and Rhythm Structure
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    Chapter 8 Automatic Reduction of MIDI Files Preserving Relevant Musical Content
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    Chapter 9 Automatic Synchronization between Audio and Partial Music Score Representation
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    Chapter 10 Automatic Image Tagging Using Community-Driven Online Image Databases
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    Chapter 11 Geo-temporal Structuring of a Personal Image Database with Two-Level Variational-Bayes Mixture Estimation
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    Chapter 12 Unsupervised Clustering in Personal Photo Collections
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    Chapter 13 Towards a Fully MPEG-21 Compliant Adaptation Engine: Complementary Description Tools and Architectural Models
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    Chapter 14 Mobile Museum Guide Based on Fast SIFT Recognition
Attention for Chapter 3: A Poset Based Approach for Condition Weighting
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Summary
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Chapter title
A Poset Based Approach for Condition Weighting
Chapter number 3
Book title
Adaptive Multimedia Retrieval. Identifying, Summarizing, and Recommending Image and Music
Published by
Springer, Berlin, Heidelberg, June 2008
DOI 10.1007/978-3-642-14758-6_3
Book ISBNs
978-3-64-214757-9, 978-3-64-214758-6
Authors

David Zellhöfer, Ingo Schmitt

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