{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T10:52:07Z","timestamp":1762253527411},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7]]},"abstract":"<jats:p>In this paper, we explore the issue of inconsistency handling over prioritized knowledge bases (KBs), which consist of an ontology, a set of facts, and a priority relation between conflicting facts. In the database setting, a closely related scenario has been studied and led to the definition of  three different notions of optimal repairs (global, Pareto, and completion) of a prioritized inconsistent database. After transferring the notions of globally-, Pareto- and completion-optimal repairs to our setting, we study the data complexity of the core reasoning tasks: query entailment under inconsistency-tolerant semantics based upon optimal repairs, existence of a unique optimal repair, and enumeration of all optimal repairs. Our results provide a nearly complete picture of the data complexity of these tasks for ontologies formulated in common DL-Lite dialects. The second contribution of our work is to clarify the relationship between optimal repairs and different notions of extensions for (set-based) argumentation frameworks. Among our results, we show that Pareto-optimal repairs correspond precisely to stable extensions (and often also to preferred extensions), and we propose a novel semantics for prioritized KBs which is inspired by grounded extensions and enjoys favourable computational properties. Our study also yields some results of independent interest concerning preference-based argumentation frameworks.<\/jats:p>","DOI":"10.24963\/kr.2020\/15","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T00:39:16Z","timestamp":1597883956000},"page":"141-151","source":"Crossref","is-referenced-by-count":10,"title":["Querying and Repairing Inconsistent Prioritized Knowledge Bases: Complexity Analysis and Links with Abstract Argumentation"],"prefix":"10.24963","author":[{"given":"Meghyn","family":"Bienvenu","sequence":"first","affiliation":[{"name":"CNRS & University of Bordeaux, France"}]},{"given":"Camille","family":"Bourgaux","sequence":"additional","affiliation":[{"name":"DI ENS, CNRS, ENS, PSL University, & Inria, Paris, France"}]}],"member":"10584","event":{"number":"17","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","Association for Logic Programming","Center for Perspicuous Computing","European Association for Artificial Intelligence","Ontopic - The Virtual Knowledge Graph Company"],"acronym":"KR-2020","name":"17th International Conference on Principles of Knowledge Representation and Reasoning {KR-2020}","start":{"date-parts":[[2020,9,12]]},"theme":"Artificial Intelligence","location":"Rhodes, Greece","end":{"date-parts":[[2020,9,18]]}},"container-title":["Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T16:18:31Z","timestamp":1604593111000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2020\/15"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2020\/15","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}