Fuzzy DL-Lite has been studied as a means to answer queries w.r.t. vague or imprecise knowledge and facts. Existing approaches consider only the Zadeh semantics or are limited to precise terminological knowledge, where only facts are graded. We study the problem of answering conjunctive queries over fuzzy DL-Lite ontologies which allow also graded axioms, and whose semantics is based on mathematical fuzzy logic. We show that for the Gödel t-norm, the degree of an answer is computable through repeated calls to a classical query answering engine. For non-idempotent t-norms, we show the difficulty in dealing with degrees, and provide some partial solutions.
Pasi, G., Penaloza, R. (2020). Query Answering in Fuzzy DL-Lite with Graded Axioms. In Rules and Reasoning 4th International Joint Conference, RuleML+RR 2020, Oslo, Norway, June 29 – July 1, 2020, Proceedings (pp.39-53). Springer [10.1007/978-3-030-57977-7_3].
Query Answering in Fuzzy DL-Lite with Graded Axioms
Pasi G.;Penaloza R.
2020
Abstract
Fuzzy DL-Lite has been studied as a means to answer queries w.r.t. vague or imprecise knowledge and facts. Existing approaches consider only the Zadeh semantics or are limited to precise terminological knowledge, where only facts are graded. We study the problem of answering conjunctive queries over fuzzy DL-Lite ontologies which allow also graded axioms, and whose semantics is based on mathematical fuzzy logic. We show that for the Gödel t-norm, the degree of an answer is computable through repeated calls to a classical query answering engine. For non-idempotent t-norms, we show the difficulty in dealing with degrees, and provide some partial solutions.
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