Query-Driven Repairing of Inconsistent DL-Lite Knowledge Bases
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 957-963.
Abstract
We consider the problem of query-driven repairing of inconsistent DL-Lite knowledge bases: query answers are computed under inconsistency-tolerant semantics, and the user provides feedback about which answers are erroneous or missing. The aim is to find a set of ABox modifications (deletions and additions), called a repair plan, that addresses as many of the defects as possible. After formalizing this problem and introducing different notions of optimality, we investigate the computational complexity of reasoning about optimal repair plans and propose interactive algorithms for computing such plans. For deletion-only repair plans, we also present a prototype implementation of the core components of the algorithm.
@inproceedings{ijcai2016p140,
title = {Query-Driven Repairing of Inconsistent DL-Lite Knowledge Bases},
author = {Bienvenu, Meghyn and Bourgaux, Camille and Goasdoué, François},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {957--963},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/140},
}
TY - CPAPER TI - Query-Driven Repairing of Inconsistent DL-Lite Knowledge Bases AU - Bienvenu, Meghyn AU - Bourgaux, Camille AU - Goasdoué, François T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 957 EP - 963 UR - https://ijcai.org/proceedings/2016/140 ER -Copied
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