The SOMLib Digital Library System

The SOMLib project has created a digital library system that uses a neural network-based core for the representation of the library, and uses the self-organizing map, a popular unsupervised neural network model, to topically structure a document collection similar to the organization of real-world libraries.

Abstract

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.