134540 20260217205450.0 doi 10.1016/j.eswa.2024.123838 sideral 138199 ART-2024-138199 eng Bobed, Carlos Universidad de Zaragoza (orcid)0000-0003-4239-8785 Praedixi, Redegi, Cogitavi: Adaptive knowledge for resource-aware semantic reasoning 2024 Access copy available to the general public Unrestricted Representing knowledge with ontologies and performing reasoning with semantic reasoners is important in many intelligent applications. However, existing reasoners do not take into account the available resources of the device where they run, which can be important in many scenarios such as reasoning with very large ontologies or reasoning on resource-constrained mobile devices. In this paper, we propose a novel approach to adapt the size of knowledge managed by applications, taking into account several criteria about resources available (such as time, memory, and battery consumption), at the same time. Thus, rather than giving no answer due to the lack of resources needed to deal with a full ontology, we propose a novel architecture to compute a subontology to provide an incomplete answer at least. Our approach makes use of existing approaches to predict the performance of semantic reasoners and to compute ontology modularisation and ontology partition, but taking into account the associated resource consumption. We also propose a novel measure to estimate the semantic loss when replacing the original ontology by a subontology. Finally, we present an implementation and evaluation of the whole pipeline, showing that the semantic loss incurred in the process is acceptable. info:eu-repo/grantAgreement/ES/AEI/PID2020-113903RB-I00 info:eu-repo/grantAgreement/ES/DGA/T42-23R info:eu-repo/semantics/openAccess by-nc-nd https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es 7.5 2024 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 28 / 204 = 0.137 2024 Q1 T1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 7 / 106 = 0.066 2024 Q1 T1 ENGINEERING, ELECTRICAL & ELECTRONIC 37 / 368 = 0.101 2024 Q1 T1 1.854 2024 Artificial Intelligence 2024 Q1 Engineering (miscellaneous) 2024 Q1 Computer Science Applications 2024 Q1 15.0 2024 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Bobillo, Fernando Universidad de Zaragoza (orcid)0000-0001-5136-4152 Jiménez-Ruiz, Ernesto Mena, Eduardo Universidad de Zaragoza (orcid)0000-0002-7462-0080 Pan, Jeff Z. 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 250 (2024), 123838 [14 pp.] Expert syst. appl. Expert Systems with Applications 0957-4174 1144977 http://zaguan.unizar.es/record/134540/files/texto_completo.pdf Postprint 1321172 http://zaguan.unizar.es/record/134540/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:134540 articulos driver 2026-02-17-20:18:52 ARTICLE