Evaluation of feature measures and similarity measures for content-based retrieval

Abstract

Evaluation is a critical issue in any information systems. This problem has become more and more important with the rapid development of multimedia systems. Feature measures and similarity measures play a central role in content-based retrieval. Evaluation of their effectiveness and efficiency then become a key issue in assessing the performance of a content-based multimedia system. A learning algorithm has been studied to find a suitable and hopefully the best similarity function for a given set of feature measure and a given set of training data set.