Black magic meta data - Get a glimpse behind the scene

This paper presents how we utilise natural language processing techniques in order to "automagically" classify information stored in a CRIS, and aggregate the information in a researchers portfolio into a "fingerprint" describing a researchers research interest. Our approach exploits the fact that entities in a CRIS typically include some kind of text - most notable example being publication abstracts. We explain how the approach can result in automatic detailed classification of information, and argue how we can take advantage of such information in order to facilitate networking. Finally, we describe how we have realised the solution within our CRIS system.