Terminology-driven literature mining and knowledge acquisition in biomedicine.
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.
Nenadić
Goran
G
Computer Science Department, University of Salford, Salford, UK.
Mima
Hideki
H
Spasić
Irena
I
Ananiadou
Sophia
S
Tsujii
Jun-ichi
J
D001185:Artificial Intelligence; D006801:Humans; D019451:Information Management; D007256:Information Systems; D016490:Integrated Advanced Information Management Systems; D008037:Linguistics; D016239:MEDLINE; D008962:Models, Theoretical; D009323:Natural Language Processing; D012984:Software; D009626:Terminology as Topic