Knowledge Discovery Approach Based on Closeness Relationship of FC

A fuzzy clustering is one of important and valid methods to knowledge discovery. One of problems in fuzzy clustering is to determine a certain fuzzy sample classification in given limited sample space. Another is its validity, that is to say, if the sample is resemble in sample space, its fuzzy type will be resemble too. In our research, firstly, using triangle arithmetic operator and triangle transference, we extend fuzzy equivalence relationship to fuzzy closeness relationship, and cluster. Secondly, importing fuzzy coverage based on fuzzy closeness relationship, we judge resemble type of resemble sample. Thirdly, we introduce the clustering method based on fuzzy closeness relationship and fuzzy coverage. The method can overcome information more loss in fuzzy equivalence. Finally, evaluating its validity, we test its feasibility. The method above is applied to knowledge discovery for electronic commerce on Internet, we have got good result.