Measuring similarity in ontologies: A new family of measures

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Abstract

Several attempts have been already made to develop similarity measures for ontologies. We noticed that some existing similarity measures are ad-hoc and unprincipled. In addition, there is still a need for similarity measures which are applicable to expressive Description Logics and which are terminological. To address these requirements, we have developed a new family of similarity measures. Two separate empirical studies have been carried out to evaluate the new measures. First, we compare the new measures along with some existing measures against a gold-standard. Second, we examine the practicality of using the new measures over an independently motivated corpus of ontologies.

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APA

Alsubait, T., Parsia, B., & Sattler, U. (2014). Measuring similarity in ontologies: A new family of measures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8876, pp. 13–25). Springer Verlag. https://doi.org/10.1007/978-3-319-13704-9_2

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