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РецензированоEN2012

Assistive Tagging: A Survey of Multimedia Tagging with Human-Computer Joint Exploration

Meng Wang · Bingbing Ni · Xian-Sheng Hua

Научные статьи · 2012

Аннотация

Along with the explosive growth of multimedia data, automatic multimedia tagging has attracted great interest of various research communities, such as computer vision, multimedia, and information retrieval. However, despite the great progress achieved in the past two decades, automatic tagging technologies still can hardly achieve satisfactory performance on real-world multimedia data that vary widely in genre, quality, and content. Meanwhile, the power of human intelligence has been fully demonstrated in the Web 2.0 era. If well motivated, Internet users are able to tag a large amount of multimedia data. Therefore, a set of new techniques has been developed by combining humans and computers for more accurate and efficient multimedia tagging, such as batch tagging, active tagging, tag recommendation, and tag refinement. These techniques are able to accomplish multimedia tagging by jointly exploring humans and computers in different ways.

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«Along with the explosive growth of multimedia data, automatic multimedia tagging has attracted great interest of various research communities, such as computer vision, multimedia, and information retrieval.»

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Along with the explosive growth of multimedia data, automatic multimedia tagging has attracted great interest of various research communities, such as computer vision, multimedia, and information retrieval. Полный текст публикации CiteX не хранит — доступ к первоисточнику открывается по DOI согласно лицензии издателя и выбранному плану.

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