The Journal of Machine Learning Research
Generic image classification using visual knowledge on the web
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Image region entropy: a measure of "visualness" of web images associated with one concept
Proceedings of the 13th annual ACM international conference on Multimedia
Web image mining towards universal age estimator
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Correlated multi-label refinement for semantic noise removal
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
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We propose measuring "visualness" of concepts with images on the Web, that is, what extent concepts have visual characteristics. This is a new application of "Web image mining". To know which concept has visually discriminative power is important for image recognition, since not all concepts are related to visual contents. Mining image data on the Web with our method enables it. Our method performs probabilistic region selection for images and computes an entropy measure which represents "visualness" of concepts. In the experiments, we collected about forty thousand images from the Web for 150 concepts. We examined which concepts are suitable for annotation of image contents.