基于本体片段模糊相似度的异构本体合并

Heterogeneous Ontology Merging Based on Ontology Slice Fuzzy Similarity

提出一种基于本体片段模糊相似度的异构本体合并方法研究。复杂的异构本体模型可被分割成多个本体片段,且这些片段均具有独立语义,使本体合并转换成本体片段之间的合并;提出基于概念或关系的两种本体片段模糊化相似度计算方法,并进一步讨论一种基于本体片段模糊相似度的异构本体合并的算法。该算法解决相似度计算过程中出现的模糊特性过早裁决的问题,从而文本信息可与结构信息共同分析以提高本体片段间的合并效果。最后通过应用实例和相关复杂性分析比较,全面评估该基于本体片段模糊相似度的异构本体合并的算法。

This paper presents a novel heterogeneous ontology merging approach based on the fuzzy similarity between ontology slices. The ontology model to be merged is divided into many slices having independent semantic meaning, and the merging between ontology models can be transferred to the merging between ontology slices. Two kinds of fuzzy similarity algo- rithms between ontology slices are proposed based on the concept and relation of ontology, anda heterogeneous ontology merging approach based on fuzzy similarity between ontology slices is discussed. It restrains possibility of making decision to fuzzy characteristic too early in the process of similarity calculation. The structural information can be synchronously analyzed and computed together with text information to improve the effect of merging between ontology slices. The proposed approach is evaluated by an ontology merging application example and re- lated analyses and comparisons.