The Fuzzy Semantic Relations in Semantic Link Network

The Semantic Link Network (SLN) is a directed network consisting of semantic nodes and semantic links between nodes. A semantic link directed from one node to another can be represented as a pointer labeled with a semantic relation. Since the proposed of SLN, it gets widely used, and increasingly becomes a study hotspot. SLN do not consider the fuzzy of semantic nodes and semantic relations, so that it can not express the fuzzy semantics, which leads to lack of accuracy. This shortcoming is more obvious when we apply SLN in the domain of image retrieval and community detection. This paper introduced fuzzy theory into SLN, proposed a five-layer fuzzy-based model for Fuzzy Semantic Link Network, and used the fuzzy degree to measure the fuzzy semantics relations. The experiment results showed that the application of F_SLN to image retrieval is effective, when dealing with fuzzy issues.