Ontology-based semantic similarity measures for product-service system design

Today's organization face a considerable challenge in making effective use of increasing amounts of information that often accumulates and remains in paper reports. Specifically, the use of accumulated knowledge in solving product-service systems remains a challenge. One approach is to use case-based reasoning (CBR) in which problems are solved “by using or adapting solutions to old problems”. In CBR, a case is both a representation of the problem and a solution to that problem. Case-based reasoning uses similarity measures to identify cases which are more relevant to the problem to be solved. Specifically, most non-numeric similarity measures are based on syntactic grounds. However, syntax-based similarity measures often fail to produce good matches when confronted with the meaning associated to the words they compare. Ontologies can be used to produce similarity measures that are based on semantics as a way to overcome the limitations of syntactic similarity measures. This paper investigates semantic similarity measures based on the comparison of classes in an ontology by using attribute information obtained with formal concept analysis.