Similarity measures for FL0 concept descriptions from an automata-theoretic point of view

In Description Logics (DLs), information in knowledge bases (KBs) is captured by concept descriptions. The traditional reasoning problem of subsumption has been proven indispensable in DL systems and applications. However, when no subsumption relationship between two concepts is identified, no classification relationship among the two concepts can be given. In this work, we present novel semantic similarity measures for the small language FL
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. The measures are derived from the structural characterization subsumption considered from an automata-theoretic point of view. The proposed concept of semantic similarity measures for the language FL
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computes a numerical degree of similarity between two FL
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concept descriptions w.r.t. unfoldable terminologies.