A context-aware semantic similarity model for ontology environments
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While many researchers have contributed to the field of semantic similarity models so far, we find that most of the models are designed for the semantic network environment. When applying the semantic similarity model within the semantic-rich ontology environment, two issues are observed: (1) most of the models ignore the context of ontology concepts and (2) most of the models ignore the context of relations. Therefore, in this paper, we present a solution for the two issues, including a novel ontology conversion process and a context-aware semantic similarity model, by considering the factors of both the context of concepts and relations, and the ontology structure. Furthermore, in order to evaluate this model, we compare its performance with that of several existing models' performance in a large-scale knowledge base, and the evaluation result preliminarily proves the technical advantage of our model in ontology environments. Conclusions and future works are described in the final section.
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