Ontology Similarity in the Alignment Space

Abstract

Abstract. Measuring similarity between ontologies can be very useful for different purposes, e.g., finding an ontology to replace another, or finding an ontology in which queries can be translated. Classical measures compute similarities or distances in an ontology space by directly comparing the content of ontologies. We introduce a new family of ontology measures computed in an alignment space: they evaluate the similarity between two ontologies with regard to the available alignments between them. We define two sets of such measures relying on the existence of a path between ontologies or on the ontology entities that are preserved by the alignments. The former accounts for known relations between ontologies, while the latter reflects the possibility to perform actions such as instance import or query translation. All these measures have been implemented in the OntoSim library, that has been used in experiments which showed that entity preserving measures are comparable to the best ontology space measures. Moreover, they showed a robust behaviour with respect to the alteration of the alignment space.

Introducing the new SIM-DL A semantic similarity measurement plug-in for the Protégé ontology editor

“…While similarity is at the core of most work on ontology alignment [8] and also implemented in semantic-based information retrieval interfaces [18], it is still not very popular in the broader Semantic Web community. We believe that Linked Data and an increasing number of small, applicationdriven ontologies will boost the acceptance and need for similarity reasoning and the provided relevance ranking.…”

Reconciling Schema Matching Networks Through Crowdsourcing

“…A somewhat related concept of alignment space was introduced in Euzenat [44]. The authors consider a network of ontologies and alignments between them, which is similar to our setting, however unlike us, they do not consider network-aware consistency conditions.…”

An Empirical Study of Vocabulary Relatedness and Its Application to Recommender Systems

“…Further, the similarities among a collection of vocabularies can be represented as a graph, on which statistical analysis [10,21] and complex network analysis [12] have been carried out. Besides, more sophisticated measures of similarity have been established based on such graph [6]. In our work, we also implement content-based similarity as one aspect, when we deal with the more general notion of relatedness.…”