In this thesis work we develop and test MOGO (a Mini-Ontology GeneratOr.) MOGO automates the generation of mini-ontologies from canonicalized tables of data. This will help anyone trying to organize large amounts of existing data into a more searchable and accessible form. By using a number of different heuristic rules for selecting, enhancing, and modifying ontology elements, MOGO allows users to automatically, semi-automatically, or manually generate conceptual mini-ontologies from canonicalized tables of data. Ideally, MOGO operates fully automatically while allowing users to intervene to direct and correct when necessary so that they can always satisfactorily complete the translation of canonicalized tables into mini-ontologies. Experimental results show that MOGO is able to automatically identify the concepts, relationships, and constraints that exist in arbitrary tables of values with a relatively high level of accuracy. This automation significantly reduces the work required to translate canonicalized tables into mini-ontologies.
College and Department
Physical and Mathematical Sciences; Computer Science
BYU ScholarsArchive Citation
Lynn, Stephen G., "Automating Mini-Ontology Generation from Canonical Tables" (2008). Theses and Dissertations. 1381.
ontology, tango, conceptual model