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dc.contributor.authorLukasiewicz, T
dc.contributor.authorMalizia, E
dc.contributor.authorVaicenavicius, A
dc.date.accessioned2018-11-15T13:12:37Z
dc.date.issued2019-07-17
dc.description.abstractQuerying inconsistent ontological knowledge bases is an important problem in practice, for which several inconsistencytolerant query answering semantics have been proposed, including query answering relative to all repairs, relative to the intersection of repairs, and relative to the intersection of closed repairs. In these semantics, one assumes that the input database is erroneous, and the notion of repair describes a maximally consistent subset of the input database, where different notions of maximality (such as subset and cardinality maximality) are considered. In this paper, we give a precise picture of the computational complexity of inconsistencytolerant (Boolean conjunctive) query answering in a wide range of Datalog± languages under the cardinality-based versions of the above three repair semantics.en_GB
dc.description.sponsorshipThis work was supported by the Alan Turing Institute under the UK EPSRC grant EP/N510129/1, and by the EPSRC grants EP/R013667/1, EP/L012138/1, and EP/M025268/1.en_GB
dc.identifier.citationVol. 33 (1), pp. 2962-2969
dc.identifier.doi10.1609/aaai.v33i01.33012962
dc.identifier.urihttp://hdl.handle.net/10871/34776
dc.language.isoenen_GB
dc.publisherAAAI Pressen_GB
dc.rights.embargoreasonUnder embargo until 2 February 2019en_GB
dc.rights© 2019 AAAI Pressen_GB
dc.titleComplexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Cardinality-Based Repairsen_GB
dc.typeArticleen_GB
dc.contributor.editorVan Hentenryck, Pen_GB
dc.contributor.editorZhou, Z-Hen_GB
dc.descriptionThis is the author accepted manuscript. The final version is available from Association for the Advancement of Artificial Intelligence (AAAI) via the DOI in this recorden_GB
dc.descriptionAAAI-19: 33rd AAAI Conference on Artificial Intelligence, 27 January - 1 February 2019, Honolulu, Hawaii, USA
dc.identifier.journalProceedings of the AAAI Conference on Artificial Intelligence


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