Learning to construct knowledge bases from the World Wide Web
Artificial Intelligence - Special issue on Intelligent internet systems
Evaluating ontological decisions with OntoClean
Communications of the ACM - Ontology: different ways of representing the same concept
Dictionary of Computing
Extraction and use of linguistic patterns for modelling medical guidelines
Artificial Intelligence in Medicine
Automated ontology construction for unstructured text documents
Data & Knowledge Engineering
Using semantic dependencies for consistency management of an ontology of brain-cortex anatomy
Artificial Intelligence in Medicine
Automatic ontology extraction from unstructured texts
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II
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Corpus linguistic methods are discussed in the context of the automatic extraction of a candidate terminology of a specialist domain of knowledge. Collocation analysis of the candidate terms leads to some insight into the ontological commitment of the domain community or collective. The candidate terminology and ontology can be easily verified and validated and subsequently may be used in the construction of information extraction systems and of knowledge-based systems. The use of the methods is illustrated by an investigation of the ontological commitment of four major collectives: nuclear physics, cell biology, linguistics and anthropology. An analysis of a diachronic corpus allows an insight into changes in basic concepts within a specialism; an analysis of a corpus comprising texts published during a short and fixed time period ---a synchronic corpus- shows how different sub-specialisms within a collective commit themselves to an ontology.