Linked Data Based Approach to Similarity Reasoning
Innovation generally starts from a creative idea, triggered by a specific problem requesting a non-trivial solution or from an offered opportunity, e.g., by new technological solutions. SemSim is a semantic similarity reasoning method that has been conceived to be used as a service for the Semantic Web. SemSim is based on a weighted reference ontology, which is used to semantically annotate a collection of digital resources (e.g., documents) to be searched. In this paper, the authors present a new approach to SemSim implementation based on linked data, that significantly increments its usability in the semantic Web.