Adding machine learning and knowledge intensive techniques to a digital library service

Abstract

This paper presents IDL, a prototypical digital library service. It integrates machine learning tools and intelligent techniques in order to make effective, efficient and economically feasible the process of capturing the information that should be stored and indexed by content in the digital library. In fact, information capture and semantic indexing are critical issues when building a digital library, since they involve complex pattern recognition problems, such as document analysis, classiffication and understanding. Experimental results show that learning systems can effectively and efficiently solve all these problems.