SOMLib: A Digital Library System Based on Neural Networks

Digital Libraries have gained tremendous interest with numerous 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 create a digital library system that uses a neural network-based core for library representation and query processing. The self-organizing map, a popular unsupervised neural network model, is used to automatically structure a document collection. Based on this core, additional modules integrate distributed libraries and create an intuitive representation of the library, automatically labeling the various topical sections in the document collection. Keywords Self-Organizing Map (SOM), Document Clustering, Visualization, Distributed Digital Libraries

• Type: Conference
• Year: 1999
• Where: DL
• Authors: Andreas Rauber, Dieter Merkl
• Keywords: Digital Libraries, Digital Library, DL 1999, Document Collection, Self-Organizing Map