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An Evaluation Method for Ontology Complexity Analysis in Ontology Evolution

Authors: Dalu Zhang; Chuan Ye; Zhe Yang 0003;

An Evaluation Method for Ontology Complexity Analysis in Ontology Evolution

Abstract

Ontology evolution becomes extremely important with the tremendous application of ontology. Ontology's size and complexity change a lot during its evolution. Thus it's important for ontology developers to analyze and try to control ontology's complexity to ensure the ontology is useable. In this paper, an evaluation method for analyzing ontology complexity is suggested. First, we sort all the concepts of an ontology according to their importance degree (a definition we will give below), then by using a well-defined metrics suite which mainly examines the concepts and their hierarchy and the quantity, ratio of concepts and relationships, we analyze the evolution and distribution of ontology complexity. In the study, we analyzed different versions of GO ontology by using our evaluation method and found it works well. The results indicate that the majority of GO's complexity is distributed on the minority of GO's concepts, which we call “important concepts” and the time when GO's complexity changed greatly is also the time when its “important concepts” changed greatly.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Average
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