Answering Fuzzy Conjunctive Queries over Finitely Valued Fuzzy Ontologies
Fuzzy Description Logics (DLs) provide a means for representing vague knowledge about an application domain. In this paper, we study fuzzy extensions of conjunctive queries (CQs) over the DL $\mathcal{SROIQ}$ based on finite chains of degrees of truth. To answer such queries, we extend a well-known...
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creator | Borgwardt, Stefan Mailis, Theofilos Peñaloza, Rafael Turhan, Anni-Yasmin |
description | Fuzzy Description Logics (DLs) provide a means for representing vague
knowledge about an application domain. In this paper, we study fuzzy extensions
of conjunctive queries (CQs) over the DL $\mathcal{SROIQ}$ based on finite
chains of degrees of truth. To answer such queries, we extend a well-known
technique that reduces the fuzzy ontology to a classical one, and use classical
DL reasoners as a black box. We improve the complexity of previous reduction
techniques for finitely valued fuzzy DLs, which allows us to prove tight
complexity results for answering certain kinds of fuzzy CQs. We conclude with
an experimental evaluation of a prototype implementation, showing the
feasibility of our approach. |
doi_str_mv | 10.48550/arxiv.1508.02626 |
format | Article |
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knowledge about an application domain. In this paper, we study fuzzy extensions
of conjunctive queries (CQs) over the DL $\mathcal{SROIQ}$ based on finite
chains of degrees of truth. To answer such queries, we extend a well-known
technique that reduces the fuzzy ontology to a classical one, and use classical
DL reasoners as a black box. We improve the complexity of previous reduction
techniques for finitely valued fuzzy DLs, which allows us to prove tight
complexity results for answering certain kinds of fuzzy CQs. We conclude with
an experimental evaluation of a prototype implementation, showing the
feasibility of our approach.</description><identifier>DOI: 10.48550/arxiv.1508.02626</identifier><language>eng</language><subject>Computer Science - Artificial Intelligence ; Computer Science - Logic in Computer Science</subject><creationdate>2015-08</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1508.02626$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1508.02626$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Borgwardt, Stefan</creatorcontrib><creatorcontrib>Mailis, Theofilos</creatorcontrib><creatorcontrib>Peñaloza, Rafael</creatorcontrib><creatorcontrib>Turhan, Anni-Yasmin</creatorcontrib><title>Answering Fuzzy Conjunctive Queries over Finitely Valued Fuzzy Ontologies</title><description>Fuzzy Description Logics (DLs) provide a means for representing vague
knowledge about an application domain. In this paper, we study fuzzy extensions
of conjunctive queries (CQs) over the DL $\mathcal{SROIQ}$ based on finite
chains of degrees of truth. To answer such queries, we extend a well-known
technique that reduces the fuzzy ontology to a classical one, and use classical
DL reasoners as a black box. We improve the complexity of previous reduction
techniques for finitely valued fuzzy DLs, which allows us to prove tight
complexity results for answering certain kinds of fuzzy CQs. We conclude with
an experimental evaluation of a prototype implementation, showing the
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knowledge about an application domain. In this paper, we study fuzzy extensions
of conjunctive queries (CQs) over the DL $\mathcal{SROIQ}$ based on finite
chains of degrees of truth. To answer such queries, we extend a well-known
technique that reduces the fuzzy ontology to a classical one, and use classical
DL reasoners as a black box. We improve the complexity of previous reduction
techniques for finitely valued fuzzy DLs, which allows us to prove tight
complexity results for answering certain kinds of fuzzy CQs. We conclude with
an experimental evaluation of a prototype implementation, showing the
feasibility of our approach.</abstract><doi>10.48550/arxiv.1508.02626</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Artificial Intelligence Computer Science - Logic in Computer Science |
title | Answering Fuzzy Conjunctive Queries over Finitely Valued Fuzzy Ontologies |
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