IJIST) offers a venue to collect: 1) novel ideas for multimedia information organization, 2) interesting techniques in artificial intelligence, computer vision, data mining, and machine learning for specific tasks in multimedia information retrieval, 3) effective and efficient methods for multimedia information representation, and 4) practical applications of the above.
It has demonstrated the urgency of practically applicable techniques in multimedia information retrieval by the recent vehement competition between Microsoft and Google on search engines. This is arisen from the explosive growth of multimedia databases in both size and variety. Therefore, effective and efficient techniques on indexing, retrieval, annotation, and feedback become to be more and more important in recent years.
The past years witnessed very significant contributions of techniques in artificial intelligence, computer vision, data mining, and machine learning for multimedia information organization. For example, the support vector machine for small samples learning, the random sampling technique to reduce the training set imbalance problem, the active learning for feedback samples selection, the density estimation and machine translation for image annotation, statistical discriminant analysis for feature selection and data visualization, the semi-supervised learning for improving retrieval precision, the convex optimization for metric learning, graph cut for image segmentation and object extraction, and the local descriptors for image representation.
This special issue attracted submissions from nine countries and regions including USA,