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A Tableau-Based Forgetting in ALCQ

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Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data (CCKS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 650))

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Abstract

Forgetting is a useful tool for tailoring ontologies by reducing the number of concepts and roles. The issue of forgetting for general ontologies in more expressive description logics, such as \(\mathcal {ALCQ}\) and \(\mathcal {SHIQ}\), is largely unexplored. In this paper, we develop a decidable, sound, and complete tableau-based algorithm to implement the forgetting-based reasoning. Our tableau algorithm is technically feasibly extended to explore the forgetting in more expressive ontology languages.

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References

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Acknowledgments

This work is supported by the program of Applied Mathematics Discipline of Shanghai Polytechnic University (XXKPY1604) and the open funding project of Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education.

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Correspondence to Xiaowang Zhang .

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© 2016 Springer Nature Singapore Pte Ltd.

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Fang, H., Zhang, X. (2016). A Tableau-Based Forgetting in ALCQ. In: Chen, H., Ji, H., Sun, L., Wang, H., Qian, T., Ruan, T. (eds) Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data. CCKS 2016. Communications in Computer and Information Science, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-10-3168-7_11

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  • DOI: https://doi.org/10.1007/978-981-10-3168-7_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3167-0

  • Online ISBN: 978-981-10-3168-7

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