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Exploring multimedia in a keyword space

Magalhães, João; Ciravegna, Fabio and Rüger, Stefan (2008). Exploring multimedia in a keyword space. In: Proceeding of the 16th ACM international conference on Multimedia - MM '08, p. 101.

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We address the problem of searching multimedia by semantic similarity in a keyword space. In contrast to previous research we represent multimedia content by a vector of keywords instead of a vector of low-level features. This vector of keywords can be obtained through user manual annotations or computed by an automatic annotation algorithm. In this setting, we studied the influence of two aspects of the search by semantic similarity process: (1) accuracy of user keywords versus automatic keywords and (2) functions to compute semantic similarity between keyword vectors of two multimedia documents. We consider these two aspects to be crucial in the design of a keyword space that can exploit social-media information and can enrich applications such as Flickr and YouTube. Experiments were performed on an image and a video dataset with a large number of keywords, with different similarity functions and with two annotation methods. Surprisingly, we found that multimedia semantic similarity with automatic keywords performs as good as or better than 95% accurate user keywords.

Item Type: Conference or Workshop Item
Copyright Holders: 2008 ACM
Keywords: search; multimedia; user keyword annotations; automatic keyword annotations; keyword spaces
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 25885
Depositing User: Kay Dave
Date Deposited: 04 Jan 2011 11:54
Last Modified: 14 Dec 2018 10:25
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