|Title||OntoQA: Metric-Based Ontology Quality Analysis|
|Publication Type||Conference Paper|
|Year of Publication||2005|
|Authors||Boanerges Aleman-Meza, Amit Sheth, Michael Moore, Samir Tartir, Ismailcem Budak Arpinar|
|Conference Name||IEEE ICDM 2005 Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources|
|Conference Location||Houston, TX|
As the Semantic Web gains importance for sharing knowledge on the Internet this has lead to the development and publishing of many ontologies in different domains. When trying to reuse existing ontologies into their applications, users are faced with the problem of determining if an ontology is suitable for their needs. In this paper, we introduce OntoQA, an approach that analyzes ontology schemas and their populations (i.e. knowledgebases) and describes them through a well defined set of metrics. These metrics can highlight key characteristics of an ontology schema as well as its population and enable users to make an informed decision quickly. We present an evaluation of several ontologies using these metrics to demonstrate their applicability.
|Full Text|| |
Samir Tartir, I. Budak Arpinar, Michael Moore, Amit P. Sheth, and Boanerges Aleman-Meza, 'OntoQA: Metric-Based Ontology Quality Analysis,' IEEE ICDM 2005 Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources, Houston, TX, November 27, 2005.
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