Causal Knowledge Modeling for Traditional ChineseMedicine using OWL 2

ISWC-2010 Doctoral Consortium.

计算机科学;

Peiqin Gu

Others  :  http://ceur-ws.org/Vol-660/paper4.pdf
PID  :  41976

学科分类：计算机科学（综合）

来源: CEUR

【 摘 要 】

Unlike Western Medicine, those in Traditional Chinese Medicine (TCM) are based on inherent rules or patterns, which can be considered ascausal links. Existing approaches tend to apply computational methods onsemantic ontology to do knowledge mining, but it cannot perfectly make use ofinternal principles in TCM. When it comes to knowledge representation, we cantransform this inherent knowledge into causal graphs. In this paper, we presentan approach to build a TCM knowledge model with the capability of rulereasoning using OWL 2. In particular, we focused on the causal relationsamong syndrome and symptoms, changes between syndromes. We evaluatedour approach by giving two typical use cases and implemented them using Jena,a Java framework supporting RDF, OWL, and including a rule-based inferenceengine. The evaluation results suggested that our approach clearly displayed thecausal relations in TCM and shows a great potential in TCM knowledge mining.