Notice of RetractionFuzzy Clustering Based on Quotient Space and Its Application in CRM

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

By using method of fuzzy mathematics to quantitatively determine fuzzy relationship between samples, the fuzzy clustering analysis is able to reflect the world objectively and accurately. In this paper, combing the ideas of quotient space theory, hierarchical structure and fuzzy synthetic evaluation, a new model of fuzzy clustering analysis is proposed based on quotient space, which uses theory of granularities for attributes naturalization. The method not only reduces dimensions of attributes but also takes into account all effects of the important attributes by mapping them from low levels to high levels. Additionally, a new formula is proposed for similar matrix construction. In order to reduce the blindness for determination of the categories number, the threshold process is introduced, and we can gain the cluster outcome as soon as possible by regulating the grain-size. Finally, we did customer relationship management (CRM) in application and it is proved that the model is effective and reasonable for classification of multi-dimensional data.