Issues in learning an ontology from text

Christopher Brewster, Simon Jupp, Joanne Luciano, David Shotton, Robert Stevens, Ziqi Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Ontology construction for any domain is a labour intensive and complex process. Any methodology that can reduce the cost and increase efficiency has the potential to make a major impact in the life sciences. This paper describes an experiment in ontology construction from text for the Animal Behaviour domain. Our objective was to see how much could be done in a simple and rapid manner using a corpus of journal papers. We used a sequence of text processing steps, and describe the different choices made to clean the input, to derive a set of terms and to structure those terms in a hierarchy. We were able in a very short space of time to construct a 17000 term ontology with a high percentage of suitable terms. We describe some of the challenges, especially
that of focusing the ontology appropriately given a starting point of a heterogeneous corpus.
Original languageEnglish
Title of host publicationThe 11th Annual Bio-Ontologies Meeting
EditorsPhillip Lord, Nigam Shah, Susanna-Assunta Sansone, Matthew Cockerill
Number of pages4
Publication statusPublished - 2008
Event11th Annual Bio-Ontologies Meeting - Toronto, Canada
Duration: 20 Jul 2008 → …

Conference

Conference11th Annual Bio-Ontologies Meeting
CountryCanada
CityToronto
Period20/07/08 → …

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  • Cite this

    Brewster, C., Jupp, S., Luciano, J., Shotton, D., Stevens, R., & Zhang, Z. (2008). Issues in learning an ontology from text. In P. Lord, N. Shah, S-A. Sansone, & M. Cockerill (Eds.), The 11th Annual Bio-Ontologies Meeting