A knowledge-based system for generating interaction networks from ecological data

dc.contributor.authorCoetzer, Willem
dc.contributor.authorMoodley, Deshendran
dc.contributor.authorGerber, Aurona Jacoba
dc.date.accessioned2017-10-31T09:01:33Z
dc.date.issued2017-11
dc.description.abstractSemantic heterogeneity hampers efforts to find, integrate, analyse and interpret ecological data. An application case-study is described, in which the objective was to automate the integration and interpretation of heterogeneous, flower-visiting ecological data. A prototype knowledge-based system is described and evaluated. The system's semantic architecture uses a combination of ontologies and a Bayesian network to represent and reason with qualitative, uncertain ecological data and knowledge. This allows the high-level context and causal knowledge of behavioural interactions between individual plants and insects, and consequent ecological interactions between plant and insect populations, to be discovered. The system automatically assembles ecological interactions into a semantically consistent interaction network (a new design of a useful, traditional domain model). We discuss the contribution of probabilistic reasoning to knowledge discovery, the limitations of knowledge discovery in the application case-study, the impact of the work and the potential to apply the system design to the study of ecological interaction networks in general.en_ZA
dc.description.departmentInformaticsen_ZA
dc.description.embargo2018-11-01
dc.description.librarianhj2017en_ZA
dc.description.urihttp://www.elsevier.com/ locate/dataken_ZA
dc.identifier.citationCoetzer, W., Moodley, D. & Gerber, A. 2017, 'A knowledge-based system for generating interaction networks from ecological data', Data and Knowledge Engineering, vol. 112, pp. 55-78.en_ZA
dc.identifier.issn0169-023X (print)
dc.identifier.issn1872-6933 (online)
dc.identifier.other10.1016/j.datak.2017.09.005
dc.identifier.urihttp://hdl.handle.net/2263/62982
dc.language.isoenen_ZA
dc.publisherElsevieren_ZA
dc.rights© 2017 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Data and Knowledge Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Data and Knowledge Engineering, vol. 112, pp. 55-78, 2017. doi : 10.1016/j.datak.2017.09.005.en_ZA
dc.subjectSemantic heterogeneityen_ZA
dc.subjectOntologiesen_ZA
dc.subjectBayesian networken_ZA
dc.subjectKnowledge discoveryen_ZA
dc.subjectSemantic architectureen_ZA
dc.subjectInteraction networken_ZA
dc.subjectEcological interactionsen_ZA
dc.subjectData miningen_ZA
dc.subjectEcologyen_ZA
dc.subjectNetwork architectureen_ZA
dc.subjectKnowledge based systemsen_ZA
dc.subjectDomain modelen_ZA
dc.subjectEcological dataen_ZA
dc.subjectEcological interaction networksen_ZA
dc.subjectProbabilistic reasoningen_ZA
dc.titleA knowledge-based system for generating interaction networks from ecological dataen_ZA
dc.typePostprint Articleen_ZA

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Coetzer_KnowledgeBased_2017.pdf
Size:
1.71 MB
Format:
Adobe Portable Document Format
Description:
Postprint Article

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.75 KB
Format:
Item-specific license agreed upon to submission
Description: