DocumentCode
2918742
Title
Evaluation Metrics for Ontology Complexity and Evolution Analysis
Author
YANG, Zhe ; Zhang, Dalu ; YE, Chuan
Author_Institution
Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai
fYear
2006
fDate
Oct. 2006
Firstpage
162
Lastpage
170
Abstract
With the tremendous development in size, the complexity of ontology increases. Thus ontology evaluation becomes extremely important for developers to determine the fundamental characteristics of ontologies in order to improve the quality, estimate cost and reduce future maintenance. Our research examines the concepts and their hierarchy in conceptual model, the common feature of the most ontologies, which reflects the fundamental complexity. We suggest a well-defined metrics suite of complexity, which mainly examine the quantity, ratio and correlativity of concepts and relationships, to evaluate ontologies from the viewpoint of complexity and its evolution. In the study, we measure three ontologies in GO to verify our metrics. The results indicate that this metrics suite works well, and the biological process ontology is the most complex one from the view of complexity, and the molecular function ontology is the unsteadiest one from the view of evolution
Keywords
ontologies (artificial intelligence); evolution analysis; ontology complexity; ontology evaluation metrics; Biological processes; Collaborative work; Computer science; Costs; Displays; Engineering management; Evolution (biology); International collaboration; Ontologies; Peer to peer computing;
fLanguage
English
Publisher
ieee
Conference_Titel
e-Business Engineering, 2006. ICEBE '06. IEEE International Conference on
Conference_Location
Shanghai
Print_ISBN
0-7695-2645-4
Type
conf
DOI
10.1109/ICEBE.2006.48
Filename
4031647
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