Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/iswc2010/paper/432> ?p ?o. }
Showing items 1 to 13 of
13
with 100 items per page.
- 432 creator peiqin-gu.
- 432 type InProceedings.
- 432 label "Causal Knowledge Modeling for Traditional Chinese Medicine using OWL 2".
- 432 sameAs 432.
- 432 abstract "Unlike Western Medicine, those in Traditional Chinese Medicine (TCM) are based on inherent rules or patterns, which can be considered as causal links. Existing approaches tend to apply computational methods on semantic ontology to do knowledge mining, but it cannot perfectly make use of internal principles in TCM. When it comes to knowledge representation, we can transform this inherent knowledge into causal graphs. In this paper, we present an approach to build a TCM knowledge model with the capability of rule reasoning using OWL 2. In particular, we focused on the causal relations among syndrome and symptoms, changes between syndromes. We evaluated our approach by giving two typical use cases and implemented them using Jena, a Java framework supporting RDF, OWL, and including a rule-based inference engine. The evaluation results suggested that our approach clearly displayed the causal relations in TCM and shows a great potential in TCM knowledge mining.".
- 432 hasAuthorList authorList.
- 432 isPartOf proceedings.
- 432 keyword "causal knowledge modeling".
- 432 keyword "owl 2".
- 432 keyword "rule reasoning".
- 432 keyword "semantic web".
- 432 keyword "tcm".
- 432 title "Causal Knowledge Modeling for Traditional Chinese Medicine using OWL 2".