PROSE: A Plugin-Based Framework for Paraconsistent Reasoning on Semantic Web

Xiaowang Zhang, Zhiyong Feng, Wenrui Wu, Xin Wang and Guozheng Rao
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Xiaowang Zhang: School of Computer Science and Technology, Tianjin University, Tianjin, China
Zhiyong Feng: School of Computer Software, Tianjin University, Tianjin, China
Wenrui Wu: School of Computer Science and Technology, Tianjin University, Tianjin, China
Xin Wang: School of Computer Science and Technology, Tianjin University, Tianjin, China
Guozheng Rao: School of Computer Science and Technology, Tianjin University, Tianjin, China

International Journal on Semantic Web and Information Systems (IJSWIS), 2018, vol. 14, issue 1, 121-139

Abstract: The study of paraconsistent reasoning with ontologies is especially important for the Semantic Web since knowledge is not always perfect within it. However, classical OWL reasoners cannot support reasoning with inconsistent ontologies. In this article, the authors present a plugin-based framework called prose to provide rich paraconsistent reasoning services for OWL ontologies, whose architecture contains the three following parts: a classical OWL reasoner, a multi-valued transformer, and an OWL API connecting with them. Within the proposed framework prose, they implement different multi-valued paraconsistent reasoning in the OWL. Moreover, they select three popular classical OWL reasoners and two typical kinds of reasoning services for users. As the authors excepted, prose does exactly enable current classical OWL reasoners to tolerate inconsistency in a simple and convenient way. Finally, they evaluate the three reasoners in a united framework (prose) and, as a result, those results can amend the analysis of the three reasoners on inconsistent ontologies.

Date: 2018
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