کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
534464 | 870254 | 2010 | 7 صفحه PDF | دانلود رایگان |
Descriptive tags are needed to enable efficient and effective search in vast collections of images. Tag recommendation represents a trade-off between automatic image annotation techniques and manual tagging. In this letter, we formulate image tag recommendation as a maximum a posteriori (MAP) problem, making use of a visual folksonomy. A folksonomy can be seen as a collaboratively created set of metadata for informal social classification. Our experimental results show that the use of a visual folksonomy for image tag recommendation has two significant benefits, compared to a conventional approach using a limited concept vocabulary. First, our tag recommendation technique can make use of an unrestricted and rich concept vocabulary. Second, our approach is able to recommend a higher number of correct tags.
Journal: Pattern Recognition Letters - Volume 31, Issue 9, 1 July 2010, Pages 976–982