Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6862813 | Knowledge-Based Systems | 2013 | 12 Pages |
Abstract
Ontologies have currently attracted much attention of researchers and engineers in many fields such as knowledge management, etc. It is attractive for ontology engineers to select and reuse the existing ontologies by measuring and evaluating them because ontology construction is rather tedious and costly. In this paper, a general framework for stable semantic ontology measurement is proposed. We first clarify the concepts of syntactic, semantic and stable semantic ontology measurement. Then we present the semantic derived model (SDM) to represent the semantic model of an ontology. By rule based transformation, an ontology can be automatically transformed into its final semantic derived model (FSDM) which is unique. Furthermore, we can measure ontologies based on FSDM by analyzing the types of entities of the existing ontology metrics. The related experiments are made to illustrate that our framework can effectively excavate and stably measure the semantics of ontologies.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yinglong Ma, Ke Lu, Ying Zhang, Beihong Jin,