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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

A Framework and Positive Results for IAR-answering

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Despoina Trivela

Athens University of Economics and Business


Giorgos Stoilos

Babylon Health


Vasilis Vassalos

Athens University of Economics and Business


DOI:

10.1609/aaai.v32i1.11551


Abstract:

Inconsistency-tolerant semantics, like the IAR semantics, have been proposed as means to compute meaningful query answers over inconsistent Description Logic (DL) ontologies. So far query answering under the IAR semantics (IAR-answering) is known to be tractable only for arguably weak DLs like DL-Lite and the quite restricted EL⊥nr fragment of EL⊥. Towards providing a systematic study of IAR-answering, in the current paper we first present a general framework/algorithm for IAR-answering which applies to arbitrary DLs but need not terminate. Nevertheless, this framework allows us to develop a sufficient condition for tractability of IAR-answering and hence of termination of our algorithm. We then show that this condition is always satisfied by the arguably expressive DL DL-Litebool, providing the first positive result for IAR-answering over a non-Horn-DL. In addition, recent results show that this condition usually holds for real-world ontologies and techniques and algorithms for checking it in practice have also been studied recently; thus, overall our results are highly relevant in practice. Finally, we have provided a prototype implementation and a preliminary evaluation obtaining encouraging results.

Topics: AAAI

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Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos A Framework and Positive Results for IAR-answering Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos A Framework and Positive Results for IAR-answering AAAI 2018, .

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos (2018). A Framework and Positive Results for IAR-answering. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos. A Framework and Positive Results for IAR-answering. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos. 2018. A Framework and Positive Results for IAR-answering. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos. (2018) "A Framework and Positive Results for IAR-answering", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos, "A Framework and Positive Results for IAR-answering", AAAI, p., 2018.

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos. "A Framework and Positive Results for IAR-answering". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos. "A Framework and Positive Results for IAR-answering". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Despoina Trivela||Giorgos Stoilos||Vasilis Vassalos. A Framework and Positive Results for IAR-answering. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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