Terminology-driven literature mining and knowledge acquisition in biomedicine

Nenadic, Goran, Mima, Hideki, Spasic, Irena ORCID: https://orcid.org/0000-0002-8132-3885, Ananiadou, Sophia and Tsujii, Junichi 2002. Terminology-driven literature mining and knowledge acquisition in biomedicine. International Journal of Medical Informatics 67 (1-3) , pp. 33-48. 10.1016/S1386-5056(02)00055-2

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Abstract

In this paper we describe Tagged Information Management System (TIMS), an integrated knowledge management system for the domain of molecular biology and biomedicine, in which terminology-driven literature mining, knowledge acquisition (KA), knowledge integration (KI), and XML-based knowledge retrieval are combined using tag information management and ontology inference. The system integrates automatic terminology acquisition, term variation management, hierarchical term clustering, tag-based information extraction (IE), and ontology-based query expansion. TIMS supports introducing and combining different types of tags (linguistic and domain-specific, manual and automatic). Tag-based interval operations and a query language are introduced in order to facilitate KA and retrieval from XML documents. Through KA examples, we illustrate the way in which literature mining techniques can be utilised for knowledge discovery from documents.

Item Type:	Article
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QH Natural history > QH301 Biology
Uncontrolled Keywords:	Spasic; Terminology management; Literature mining; Information extraction; Knowledge acquisition; XML annotation
Publisher:	Elsevier
ISSN:	1386-5056
Related URLs:	http://view.ncbi.nlm.nih.gov/pubmed/1246...
Last Modified:	17 Oct 2022 09:56
URI:	https://orca.cardiff.ac.uk/id/eprint/6216

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