Conflicts Detection and Elimination of Concept Restriction in Ontology Merging

Gao-jian XU, Jie SHEN, Yao LU, Shao-wen LI, Xin LI

Abstract


Ontology plays a significant role in knowledge modeling, sharing and reusing, and the elimination of concept restriction conflicts is one of the great challenges in ontology merging. Existing in Formal Concept Analysis (FCA) or, similarity basic methods mainly focus on concept-relation hierarchy merging. However, less effort had been made for the concept restriction conflict issues, i.e. value and cardinality restriction consistency preservation. In this paper, a Description Logic (DL)- based on conflict detection and elimination approach were presented, in which a DL-based Tableau Algorithm was employed to detect all potential restriction conflicts, and syntax analysis and semantics reasoning technique were proposed to perform the value, cardinality restriction and conflicts elimination. Theoretical analysis and experimental simulation prove that the proposed method seems promising, which can effectively preserve the value and cardinality consistency in multiple related ontology merging.

Keywords


Knowledge sharing and reusing, Ontology merging, Value restriction, Cardinality restriction, Conflicts elimination


DOI
10.12783/dtcse/cst2017/12583

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