In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques f...
Users prefer to navigate subjects from organized topics in an abundance resources than to list pages retrieved from search engines. We propose a framework to cluster frequent items...
In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...
The selection of appropriate proximity measures is one of the crucial success factors of content-based visual information retrieval. In this area of research, proximity measures ar...
To improve the accuracy in terms of precision and recall of an audio information retrieval system we have created a domainspecific ontology (a collection of key concepts and their...