Property-based semantic similarity and relatedness for improving recommendation accuracy and diversity

We introduce new measures of semantic similarity and relatedness for ontological concepts, based on the properties associated to them. We consider two concepts similar if, for some properties they have in common, they also have the same values assigned to these properties. On the other hand, we consider two concepts related if they have the same values assigned to dierent properties. These measures are used in the propagation of user interest values in ontologybased user models to other similar or related concepts in the domain. We tested our algorithm in event recommendation domain and showed that property-based propagation based on similarity outperforms the standard edge-based propagation. Adding relatedness as a criterion for propagation improves diversity without sacrificing accuracy. In addition, assigning a certain relevance to each property improves the accuracy of recommendation. Finally, the property-based spreading activation is eective for cross-domain recommendation.