dc.contributor.author | Lukasiewicz, T | |
dc.contributor.author | Malizia, E | |
dc.contributor.author | Vaicenavicius, A | |
dc.date.accessioned | 2018-11-15T13:12:37Z | |
dc.date.issued | 2019-07-17 | |
dc.description.abstract | Querying 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.sponsorship | This 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.citation | Vol. 33 (1), pp. 2962-2969 | |
dc.identifier.doi | 10.1609/aaai.v33i01.33012962 | |
dc.identifier.uri | http://hdl.handle.net/10871/34776 | |
dc.language.iso | en | en_GB |
dc.publisher | AAAI Press | en_GB |
dc.rights.embargoreason | Under embargo until 2 February 2019 | en_GB |
dc.rights | © 2019 AAAI Press | en_GB |
dc.title | Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Cardinality-Based Repairs | en_GB |
dc.type | Article | en_GB |
dc.contributor.editor | Van Hentenryck, P | en_GB |
dc.contributor.editor | Zhou, Z-H | en_GB |
dc.description | This is the author accepted manuscript. The final version is available from Association for the Advancement of Artificial Intelligence (AAAI) via the DOI in this record | en_GB |
dc.description | AAAI-19: 33rd AAAI Conference on Artificial Intelligence, 27 January - 1 February 2019, Honolulu, Hawaii, USA | |
dc.identifier.journal | Proceedings of the AAAI Conference on Artificial Intelligence | |