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BMCBI
2008

Terminologies for text-mining; an experiment in the lipoprotein metabolism domain

13 years 3 months ago
Terminologies for text-mining; an experiment in the lipoprotein metabolism domain
Background: The engineering of ontologies, especially with a view to a text-mining use, is still a new research field. There does not yet exist a well-defined theory and technology for ontology construction. Many of the ontology design steps remain manual and are based on personal experience and intuition. However, there exist a few efforts on automatic construction of ontologies in the form of extracted lists of terms and relations between them. Results: We share experience acquired during the manual development of a lipoprotein metabolism ontology (LMO) to be used for text-mining. We compare the manually created ontology terms with the automatically derived terminology from four different automatic term recognition (ATR) methods. The top 50 predicted terms contain up to 89% relevant terms. For the top 1000 terms the best method still generates 51% relevant terms. In a corpus of 3066 documents 53% of LMO terms are contained and 38% can be generated with one of the methods. Conclusion...
Dimitra Alexopoulou, Thomas Wächter, Laura Pi
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Dimitra Alexopoulou, Thomas Wächter, Laura Pickersgill, Cecilia Eyre, Michael Schroeder
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