The SOMLib Digital Library System

                    Andreas Rauber, Dieter Merkl
      Institut fuer Softwaretechnik, Technische Universitaet Wien
	     Resselgasse 3/188, A--1040 Wien, Austria
       www.ifs.tuwien.ac.at/~andi    www.ifs.tuwien.ac.at/~dieter


Digital Libraries have gained tremendous interest with several research 
projects addressing the wealth of challenges in this field.
While computational intelligence systems are being used for specific tasks 
in this arena, the majority of projects relies on conventional techniques 
for the basic structure of the library itself.
With the SOMLib project we created a digital library system that 
uses a neural network-based core for the representation of the library.
The self-organizing map, a popular unsupervised neural network model, is 
used to topically structure a document collection similar to the 
organization of real-world libraries. Based on this core, additional 
modules provide information retrieval features, integrate distributed 
libraries, and automatically label the various topical sections in the 
document collection. A metaphor graphics based interface further assists 
the user in intuitively understanding the library providing an instant 
overview.

Keywords: Self-Organizing Map (SOM), Document Clustering, Learning,  
          Distributed Digital Libraries, Dublin Core Metadata, 
          Metaphore Graphics, Visualization,



A. Rauber and D. Merkl. 
The SOMLib Digital Library System
Proceedings of the 3rd Europ. Conf. on Research and Advanced Technology for Digital Libraries (ECDL'99), Paris, France, September 22. - 24. 1999, 
Lecture Notes in Computer Science (LNCS 1696), Springer, 1999.