Hyb-Tvx: A Hybrid Semantic Similarity Feature-Based Measurement for Multiple Ontologies
Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia, Nurul Aswa Omar · International Journal of Advanced Trends in Computer Science and Engineering · 2019
Semantic similarity is defined as the closeness of two concepts, based on the likeliness of their meaning.It is also more ontology-based, due to their efficiency, scalability, lack of constraints and the availability of large ontologies.However, ontology-based semantic similarity is hampered by the fact that it depends on the overall scope and detail of the background ontology.This leads to insufficient knowledge, miss-ing terms and inaccuracy.This limitation can be overcome by exploiting multiple ontologies.Semantic similarity with multiple ontologies potentially leads to better accuracy because it is able to calculate the similarity of these missing terms from the combination of multiple knowledge sources.This research aims to develop and evaluate a feature-based mechanism (Hyb-TvX) to measure semantic similarity with multiple ontologies which can improve the accuracy of the similarity.Similarity value, correlation and p-value were also used in the evalua-tion of the relationship between the concept pair of multiple ontologies.Besides that, the Hyb-TvX mechanism produces the highest correla-tion value compared to the other two methods, that is 0.759 and the result correlation is significant..