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2014 | OriginalPaper | Chapter

4. Personalized Multimedia Search

Author : Jitao Sang

Published in: User-centric Social Multimedia Computing

Publisher: Springer Berlin Heidelberg

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Abstract

Given results from multimedia content analysis and user modeling, personalized multimedia services are developed to satisfy customized needs. In this chapter, we introduce a general solution framework for personalized multimedia search. We first propose a multimodal generative model to simultaneously address tasks of multimedia content analysis and user modeling, and then present the risk minimization-based theoretical framework for personalized image search. The framework considers the noisy tag issue and enables easy incorporation of social relation.

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previous chapter User Modeling on Social Multimedia Activity
next chapter Cross-Network Social Multimedia Computing
Footnotes
1
We use topic distributions over tag words and visual descriptors to represent the topic space: \(T\) is the number of topics, \(|\fancyscript{W}|\) is the size of tag vocabulary, and \(|\fancyscript{V}|\) is the size of visual-descriptor vocabulary.
 
2
\(\varPsi _{u_1,u_2}(t), u_2\in \fancyscript{C}_{u_1}\) measures the influence strength from user \(u_2\) to \(u_1\) in the \(t\)th topic.
 
3
We assume that visual descriptor prior and tag word prior all follow uniform distribution, i.e., \(p(v_{di})=\frac{1}{|\fancyscript{V}|}\), \(p(w_{di})=\frac{1}{|\fancyscript{W}|}\).
 
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Metadata
Title
Personalized Multimedia Search
Author
Jitao Sang
Copyright Year
2014
Publisher
Springer Berlin Heidelberg
Book
User-centric Social Multimedia Computing

Print ISBN: 978-3-662-44670-6

Electronic ISBN: 978-3-662-44671-3

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-662-44671-3_4