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ComR: a combined OWL reasoner for ontology classification

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Abstract

Ontology classification, the problem of computing the subsumption hierarchies for classes (atomic concepts), is a core reasoning service provided by Web Ontology Language (OWL) reasoners. Although general-purpose OWL 2 reasoners employ sophisticated optimizations for classification, they are still not efficient owing to the high complexity of tableau algorithms for expressive ontologies. Profile-specific OWL 2 EL reasoners are efficient; however, they become incomplete even if the ontology contains only a small number of axioms that are outside the OWL 2 EL fragment. In this paper, we present a technique that combines an OWL 2 EL reasoner with an OWL 2 reasoner for ontology classification of expressive SROIQ. To optimize the workload, we propose a task decomposition strategy for identifying the minimal non-EL subontology that contains only necessary axioms to ensure completeness. During the ontology classification, the bulk of the workload is delegated to an efficient OWL 2 EL reasoner and only the minimal non-EL subontology is handled by a less efficient OWL 2 reasoner. The proposed approach is implemented in a prototype ComR and experimental results show that our approach offers a substantial speedup in ontology classification. For the wellknown ontology NCI, the classification time is reduced by 96.9% (resp. 83.7%) compared against the standard reasoner Pellet (resp. the modular reasoner MORe).

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Acknowledgements

We thank the anonymous referees for their critical comments on a previous version of this paper, which encouraged us to significantly improve the paper. This work was supported by the National Key Research and Development Program of China (2016YFB1000603), the National Natural Science Foundation of China (NSFC) (Grant No. 61672377), and the Key Technology Research and Development Program of Tianjin (16YFZCGX00210). Xiaowang Zhang is supported by Tianjin Thousand Young Talents Program.

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Authors and Affiliations

  1. School of Computer Science and Technology, Tianjin University, Tianjin, 300072, China

    Changlong Wang, Zhiyong Feng, Xiaowang Zhang, Xin Wang, Guozheng Rao & Daoxun Fu

  2. Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, 300072, China

    Changlong Wang, Zhiyong Feng, Xiaowang Zhang, Xin Wang, Guozheng Rao & Daoxun Fu

  3. School of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China

    Changlong Wang

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  1. Changlong Wang
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Correspondence to Xiaowang Zhang.

Additional information

Changlong Wang received his MS degree from Northwest Normal University, China in 2010. He is currently a PhD candidate in School of Computer Science and Technology at Tianjin University, China. His current research interests are in semantic Web, knowledge representation and reasoning, and ontology.

Zhiyong Feng received his PhD degree from Tianjin University (TJU), China in 1996. Since 1996, he has been with TJU, where he is currently a professor of the School of Computer Science and Technology. His current research interests are in knowledge engineering, service computation, and cognitive computation. He is a member of ACM and IEEE.

Xiaowang Zhang received his PhD degree from Peking University, China in 2011. Since 2015, he has been with Tianjin University, where he is currently an associate professor in School of Computer Science and Technology. His current research interests are in knowledge graph, graph databases, and knowledge representation and reasoning. He is a member of ACM and CCF.

XinWang received his PhD degree in computer science and technology from Nankai University, China in 2009. Since 2009, he has been with Tianjin University, where he is currently an associate professor in School of Computer Science and Technology. His research interests are in semantic data management, graph databases, and large-scale knowledge processing.

Guozheng Rao received his PhD degree from Tianjin University, China in 2009. Since 2000, he has been with Tianjin University, where he is currently an associate professor in School of Computer Science and Technology. His current research interests are in knowledge engineering, ontology, and semantic Web.

Daoxun Fu is currently a master student in the School of Computer Science and Technology at Tianjin University, China. His current research interests are in query answering, and knowledge representation and reasoning.

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Wang, C., Feng, Z., Zhang, X. et al. ComR: a combined OWL reasoner for ontology classification. Front. Comput. Sci. 13, 139–156 (2019). https://doi.org/10.1007/s11704-016-6397-2

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