Information capture and semantic indexing of digital libraries through machine learning techniques

Abstract

This paper presents a prototypical digital library service. It integrates machine learning tools and 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. Infact, information capture is one of the main bottleneck when building a digital library, since it involves complex pattern recognition problems, such as document analysis, classification and understanding. Experimental results show that learning systems can solve effectively and efficiently these problems.