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2011 | OriginalPaper | Chapter

Quantifying Visual-Representativeness of Social Image Tags Using Image Tag Clarity

Authors : Aixin Sun, Sourav S. Bhowmick

Published in: Social Media Modeling and Computing

Publisher: Springer London

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Abstract

Tags associated with images in various social media sharing web sites are valuable information source for superior image retrieval experiences. Due to the nature of tagging, many tags associated with images are not visually descriptive. In this chapter, we propose Image Tag Clarity to evaluate the effectiveness of a tag in describing the visual content of its annotated images, which is also known as the image tag visual-representativeness. It is measured by computing the zero-mean normalized distance between the tag language model estimated from the images annotated by the tag and the collection language model. The tag/collection language models are derived from the bag of visual-word local content features of the images. The visual-representative tags that are commonly used to annotate visually similar images are given high tag clarity scores. Evaluated on a large real-world dataset containing more than 269K images and their associated tags, we show that the image tag clarity score can effectively identify the visual-representative tags from all tags contributed by users. Based on the tag clarity scores, we have made a few interesting observations that could be used to support many tag-based applications.

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next chapter Tag-Based Social Image Search: Toward Relevant and Diverse Results
Footnotes
2
Nevertheless, we believe that the image tag clarity score is generic and can be computed using other feature representations.
 
3
Recall that both τ(t) and τ(t′) are computed purely from visual content features of their tagged images.
 
4
Note that the way we bin the tag frequencies and the number of dummy tags used for estimation of the expected tag clarity scores and their standard deviations are different from that in [11]. This leads to differences in the normalized tag clarity scores reported in Sects. 4 and 5.
 
6
The number reported here is slightly different from that reported in [1] probably due to different pre-processing. Nevertheless, the tag distribution remains similar.
 
7
One image may be annotated by multiple visual or non-visual tags, respectively.
 
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Metadata
Title
Quantifying Visual-Representativeness of Social Image Tags Using Image Tag Clarity
Authors
Aixin Sun
Sourav S. Bhowmick
Copyright Year
2011
Publisher
Springer London
Book
Social Media Modeling and Computing

Print ISBN: 978-0-85729-435-7

Electronic ISBN: 978-0-85729-436-4

Copyright Year: 2011

DOI
https://doi.org/10.1007/978-0-85729-436-4_1

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