Terminology-driven literature mining and knowledge acquisition in biomedicine

• Published in: International journal of medical informatics (Shannon, Ireland) Vol. 67; no. 1; pp. 33 - 48
• Main Authors: Nenadić, Goran, Mima, Hideki, Spasić, Irena, Ananiadou, Sophia, Tsujii, Jun-ichi
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier Ireland Ltd 04.12.2002
• Subjects: Artificial Intelligence; Humans; Information extraction; Information Management; Information Systems; Integrated Advanced Information Management Systems; Knowledge acquisition; Linguistics; Literature mining; MEDLINE; Models, Theoretical; Natural Language Processing; Software; Terminology as Topic; Terminology management; XML annotation; Terminology management; XML annotation; Information extraction; Literature mining; Knowledge acquisition
• ISSN: 1386-5056; 1872-8243
• DOI: 10.1016/S1386-5056(02)00055-2

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.