Abstract
DL-Lite is a tractable family of Description Logics that underlies the OWL-QL profile of the ontology web language, which is specifically tailored for query answering. In this paper, we consider the setting where the queried data are provided by several and potentially conflicting sources. We propose a merging approach, called “Assertional Removed Sets Fusion” (ARSF) for merging \(DL\)-\(Lite\) assertional bases. This approach stems from the inconsistency minimization principle and consists in determining the minimal subsets of assertions, called assertional removed sets, that need to be dropped from the original assertional bases in order to resolve conflicts between them. We give several merging strategies based on different definitions of minimality criteria, and we characterize the behaviour of these strategies with respect to rational properties. The last part of the paper shows how to use the notion of hitting sets for computing the assertional removed sets, and the merging outcome.
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Notes
- 1.
\((X_1, \cdots , X_n) \le _{lex} (Y_1, \cdots , Y_n)\) if \(\exists i, \, 1 \le i \le n, \;\) (i) \(X_i \le Y_i\), (ii) \(\forall j, \, 1 \le j < i \; X_i = Y_i.\)
- 2.
On each column the assertional removed sets are in bold.
- 3.
We do not consider the IC postulates [21] since they apply to belief sets and not to belief bases.
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Acknowledgements
This work is partially supported by the European project H2020-MSCA-RISE: AniAge (High Dimensional Heterogeneous Data based Animation Techniques for Southeast Asian Intangible Cultural Heritage). Zied Bouraoui was supported by CNRS PEPS INS2I MODERN.
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Benferhat, S., Bouraoui, Z., Papini, O., Würbel, E. (2019). Assertional Removed Sets Merging of DL-Lite Knowledge Bases. In: Ben Amor, N., Quost, B., Theobald, M. (eds) Scalable Uncertainty Management. SUM 2019. Lecture Notes in Computer Science(), vol 11940. Springer, Cham. https://doi.org/10.1007/978-3-030-35514-2_16
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