Abstract: Fuzzy graphs are weighted graphs whose edges are characterized by weights in the unit interval. We discuss a particular type of fuzzy graphs which are reflexive and symmetrical (undirected) and are known as proximity graphs. We discuss how we build such graphs from co-occurrence data extracted from several electronic resources, and use them to represent knowledge in an associative manner. We show that such distributed knowledge representations are useful for information retrieval, text mining, and knowledge discovery tasks which we have applied to recommendation systems, social network analysis, and knowledge discovery in Biology.

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