Abstract
The study of paraconsistent reasoning with ontologies is especially important for the Semantic Web since knowledge is not always perfect within it. Quasi-classical semantics is proven to rationally draw more meaningful conclusions even from an inconsistent ontology with the stronger inference power of paraconsistent reasoning. In our previous work, we have conceived a quasi-classical framework called prose to provide rich paraconsistent reasoning services for OWL ontologies, whose architecture contains three parts: a classical OWL reasoner, a quasi-classical transformer, and OWL API connecting with them. This paper finally implements prose where quasi-classical transformer is bulit as a plugin for paraconsistent reasoning on classical reasoners. Additionally, we select three popular classical OWL reasoners (i.e., Pellet, HermiT, and FaCT++) and two typical kinds of reasoning services (i.e., QC-consistency checking and QC-classification) for users. As we excepted, prose does exactly enable current classical OWL reasoners to tolerate inconsistency in a simple and convenient way. Furthermore, we evaluate the three reasoners in three dimensions (class, property, individual) and, as a result, those results can amend the analysis of the three reasoners on inconsistent ontologies.
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Acknowledgements
We would like to thank the anonymous reviewers for their comments which helped us to improve the paper. We gratefully acknowledge Zuoquan Lin, Kewen Wang, Guilin Qi, Yue Ma, and Guohui Xiao for discussions and their critical comments on our previous work of quasi-classical desription logics. This work is supported by the program of the National High-tech R&D Program of China (863 Program) under 2013AA013204 and the National Natural Science Foundation of China (NSFC) under 61502336, 61572353, 61373035. Xiaowang Zhang is supported by the project-sponsored by School of Computer Science and Technology in Tianjin University.
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Wu, W., Feng, Z., Zhang, X., Wang, X., Rao, G. (2016). PROSE: A Plugin-Based Paraconsistent OWL Reasoner. In: Qi, G., Kozaki, K., Pan, J., Yu, S. (eds) Semantic Technology. JIST 2015. Lecture Notes in Computer Science(), vol 9544. Springer, Cham. https://doi.org/10.1007/978-3-319-31676-5_18
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