An initial evaluation of automated organization for digital library browsing Aaron Krowne and Martin Halbert   View Paper (PDF)   Return to Tools and techniques track: browsing and visualizing collections Abstract In this article we present an evaluation of text clustering and classification methods for creating digital library browse interfaces, focusing on the particular case of collections made up of heterogeneous metadata records. This situation is common in "portal" style digital libraries, which are built by harvesting content from many disparate sources, typically using the Open Archives Protocol for Metadata Harvesting (OAI-PMH). By studying the activity of users in an experimental system, we find that taxonomies built or populated using machine-learning (or "AI") techniques provide a potentially useful avenue for browsing in this digital library scenario. ©2006 Association for Computing Machinery