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.
|Number of pages||6|
|Journal||Procedia Computer Science|
|State||Published - Jan 1 2014|
|Event||12th International Conference on Current Research Information Systems, CRIS 2014 - Rome, Italy|
Duration: May 13 2014 → May 15 2014
- CRIS systems
- Term extraction