Abstract
Several application scenarios in the Web of Data share the need to identify the commonalities between a pair of RDF resources. Motivated by such needs, we propose the definition and the computation of Least Common Subsumers (LCSs) in RDF. To this aim, we provide some original and fundamental reformulations, to deal with the peculiarities of RDF. First, we adapt a few definitions from Graph Theory to paths and connectedness in RDF-graphs. Second, we define rootedRDF-graphs (r-graphs), in order to focus on a particular resource inside an RDF-graph. Third, we change the definitions of LCSs originally set up for Description Logics to r-graphs. According to the above reformulations, we investigate the computational properties of LCS in RDF, and find a polynomial-time characterization using a form of graph composition. This result remarkably distinguishes LCSs from Entailment in RDF, which is an NP-complete graph matching problem. We then devise algorithms for computing an LCS. A prototypical implementation works as a proof-of-concept for the whole approach in three application scenarios, and shows usefulness and feasibility of our proposal. Most of our examples are taken directly from real datasets, and are fully replicable thanks to the fact that the choice about which triples are selected for the computation is made explicit and flexible.
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