A bipartite graph model for associating images and text
نویسندگان
چکیده
The joint modeling of image and textual content is even more important now because of the the availability of large databases of image-rich web pages and the tagging phenomenon. Much of the current work focused on one-way association (image to text or tags). The association is often captured by building a model with hidden variables. In this paper, we propose a simple model based on random walks on bipartite graphs for joint modeling of image and textual content. We show its effectiveness for several tasks— automatic image annotation, tag association, tag localization, and spurious tag detection. Such random walk models are useful for other tasks such as web search.
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تاریخ انتشار 2006