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A Categorization Scheme of Tag-based Folksonomy Images for Efficient Image Retrieval
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 Title & Authors
A Categorization Scheme of Tag-based Folksonomy Images for Efficient Image Retrieval
Ha, Eunji; Kim, Yongsung; Hwang, Eenjun;
 
 Abstract
Recently, folksonomy-based image-sharing sites where users cooperatively make and utilize tags of image annotation have been gaining popularity. Typically, these sites retrieve images for a user request using simple text-based matching and display retrieved images in the form of photo stream. However, these tags are personal and subjective and images are not categorized, which results in poor retrieval accuracy and low user satisfaction. In this paper, we propose a categorization scheme for folksonomy images which can improve the retrieval accuracy in the tag-based image retrieval systems. Consequently, images are classified by the semantic similarity using text-information and image-information generated on the folksonomy. To evaluate the performance of our proposed scheme, we collect folksonomy images and categorize them using text features and image features. And then, we compare its retrieval accuracy with that of existing systems.
 Keywords
folksonomy;image categorization;image classification;search system;WordNet;bag of visual word;
 Language
Korean
 Cited by
1.
Mining tag-clouds to improve social media recommendation, Multimedia Tools and Applications, 2017, 76, 20, 21157  crossref(new windwow)
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E. Ha, Y. Kim, and E. Hwang, "A Categorization Scheme for Folksonomy Images," Proc. of the 42th KIISE Winter Conference, pp. 145-147, Dec. 2015. (in Korean)

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