Giving order to image queries

Users of image retrieval systems often find it frustrating that the image they are looking for is not ranked near the top of the results they are presented. This paper presents a computational approach for ranking keyworded images in order of relevance to a given keyword. Our approach uses machine learning to attempt to learn what visual features within an image are most related to the keywords, and then provide ranking based on similarity to a visual aggregate. To evaluate the technique, a Web 2.0 application has been developed to obtain a corpus of user-generated ranking information for a given image collection that can be used to evaluate the performance of the ranking algorithm