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In this article we propose a framework that generates natural language explanations supporting the suggestions generated by a recommendation algorithm.

The cornerstone of our approach is the usage of Linked Open Data (LOD) for explanation aims. Indeed, the descriptive properties freely available in the LOD cloud (e.g., the author of a book or the director of a movie) can be used to build a graph that connects the recommendations the user received to the items she previously liked via the properties extracted from the LOD cloud. In a nutshell, our approach is based on the insight that properties describing the items the user previously liked as well as the suggestions she received can be effectively used to explain the recommendations.

Such a framework is both algorithm-independent and domain-independent, thus it can generate a natural language explanation for every kind of recommendation algorithm, and it …