Terminology-driven literature mining and knowledge acquisition in biomedicine.

Full 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.

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Author information

Author/s: Nenadic, Goran (G); Mima, Hideki (H); Spasic, Irena (I); Ananiadou, Sophia (S); Tsujii, Jun-ichi (J);

Affiliation: Computer Science Department, University of Salford, Salford, UK.

Journal and publication information

Publication Type: Comparative Study; Journal Article

Journal: International journal of medical informatics (Int J Med Inform), published in Ireland. (Language: eng)

Reference: 2002-Dec; vol 67 (issue 1-3) : pp 33-48

Dates: Created 2002/12/03; Completed 2003/04/28; Revised 2007/11/15;

PMID: 12460630, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Artificial Intelligence
Humans
Information Management
Information Systems
Integrated Advanced Information Management Systems
Linguistics

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