In this paper we propose a novel method to discover the semantics of an image within a web page and bridge the semantic gap between the image features and a user's query. Since an image is always accompanied with some text segments which are closely related to the image, we propose that the semantics of the image may be discovered from such text segments through a data mining process on these texts. Based on such recognition, we applied a text mining process on the accompany texts of an image to discover the themes of this image, which constitute the semantics of this image. The self-organizing map algorithm is first applied to cluster a set of preprocessed web pages. Based on the clustering result, we design a theme identification process to identify a set of words which constitute the semantics of an image. We performed experiments on a small set of images and obtained promising results.
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