Black Magic Meta Data - get a glimpse behind the scene

Author(s)
Keywords

current research info...

term extraction

auto-classification

fingerprinting

keywords

CERIF

Issue Date
May 14, 2014
Publisher
euroCRIS
Source
"Managing Data-Intensive Science: the Role of Research Information Systems in Realising the Digital Agenda": Proceedings of the 12th International Conference on Current Research Information Systems (2014)
Procedia Computer Science 33: 239-244 (2014)
Type
Conference Paper
Abstract
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.
Description
Delivered at the CRIS2014 Conference in Rome; published in Procedia Computer Science 33 (Jul 2014).
Contains conference paper (6 pages) and presentation (16 slides)
URI
https://dspacecris.eurocris.org/handle/11366/209
DOI
File(s)
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9_Vestdam_CRIS2014_Rome.pdf

Description
post-print version
Size

539.63 KB

Format

Adobe PDF

Checksum (MD5)

981b6a84d95e4d53a097fc5b4157b86d

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WT1_vestdam_et_al_CRIS2014.pdf

Description
presentation
Size

1.19 MB

Format

Adobe PDF

Checksum (MD5)

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