Fuzzy Semantic Web Ontology Mapping
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Fuzzy Semantic Web Ontology Mapping
6.1 Introduction The need for sharing and reusing independently developed ontologies has become even more important and attractive. Ontology reuse is now one of the important research issues in the ontology field. Ontology mapping, integration, merging, alignment and versioning are some of its subprocesses. Ontology mapping is the effective method to solve the problems of knowledge sharing and reusing across the heterogeneous ontologies in the Semantic Web (Doan et al. 2002). Note that, one common issue to these subprocesses is the problem of defining similarity relations among ontology components (Zhao et al. 2007). The current ontology mapping technologies are not sufficient for fuzzy ontologies. Therefore, with the growing number of heterogeneous fuzzy ontologies in the Semantic Web, the fuzzy ontology mapping that can handle fuzzy data becomes a research hotpot. In particular, the treatment of the semantic similarity between fuzzy concepts plays a major role in ontology mapping. On this basis, Bahri et al. (2007) proposed an approach for dealing with similarity relations in fuzzy ontologies by reducing the problem of determining similarity relations among concepts to an (un)satisfiability problem. Wang et al. (2009) proposed an approach to measure the similarity of fuzzy concepts for mapping fuzzy ontologies. This method applies fuzzy set to represent fuzzy concept, and computes fuzzy concept similarity according to the compatibility of fuzzy sets. Xu et al. (2005) proposed a framework of mapping fuzzy concepts between fuzzy ontologies. It applied the approximate concept mapping approach, extended atom fuzzy concept sets and defined the least upper bounds to reduce the searching space. It resolved the mapping problem of fuzzy concepts into finding the simplified least upper bounds for atom fuzzy concepts, and gave an algorithm for searching the simplified least upper bounds. Bakillah and Mostafavi (2011) proposed a solution to the problem of fuzzy geospatial ontology and fuzzy semantic mapping. They first provided a definition of fuzzy geospatial ontologies. Then, they proposed a new fuzzy semantic mapping approach which integrated fuzzy logic operators and predicates to reason with fuzzy concepts. Finally, they demonstrated a possible application of Z. Ma et al., Fuzzy Knowledge Management for the Semantic Web, Studies in Fuzziness and Soft Computing 306, DOI: 10.1007/978-3-642-39283-2_6, Springer-Verlag Berlin Heidelberg 2014
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6 Fuzzy Semantic Web Ontology Mapping
the fuzzy semantic mapping, which is the propagation of fuzzy queries to the relevant sources of a network. Xu et al. (2010) presented a novel method based on the Fuzzy Formal Concept Analysis (FCA) theory in order to handle vague information of ontology mapping. The ontology was first defined to model vague data, and then a fuzzy formal context was constructed with the combination of two ontologies. At last, a concept similarity measure model was proposed for improving ontology mapping. Li et al. (
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