Department of Computer Science
Dynamic sub-ontology evolution for traditional Chinese medicine web ontology
As a form of important domain knowledge, large-scale ontologies play a critical role in building a large variety of knowledge-based systems. To overcome the problem of semantic heterogeneity and encode domain knowledge in reusable format, a large-scale and well-defined ontology is also required in the traditional Chinese medicine discipline. We argue that to meet the on-demand and scalability requirement ontology-based systems should go beyond the use of static ontology and be able to self-evolve and specialize for the domain knowledge they possess. In particular, we refer to the context-specific portions from large-scale ontologies like the traditional Chinese medicine ontology as sub-ontologies. Ontology-based systems are able to reuse sub-ontologies in local repository called ontology cache. In order to improve the overall performance of ontology cache, we propose to evolve sub-ontologies in ontology cache to optimize the knowledge structure of sub-ontologies. Moreover, we present the sub-ontology evolution approach based on a genetic algorithm for reusing large-scale ontologies. We evaluate the proposed evolution approach with the traditional Chinese medicine ontology and obtain promising results.
Ontology, Traditional Chinese medicine, Sub-ontology, Knowledge, Evolutionary computation
Source Publication Title
Journal of Biomedical Informatics
This work is partially supported by subprogram of China 973 Project (No. 2003CB317006), National Science Fund for Distinguished Young Scholars of China NSF Program (No. NSFC60533040), National Key Technology R&D Program (No. 2006BAH02A01), a NSFC program under Grant No. NSFC60503018, and also a grant from ChinaGrid (CNGI-04-15-7A).
Link to Publisher's Edition
Mao, Yuxin, Zhaohui Wu, Wenya Tian, Xiaohong Jiang, and William K. Cheung. "Dynamic sub-ontology evolution for traditional Chinese medicine web ontology." Journal of Biomedical Informatics 41.5 (2008): 790-805.