An Algorithm of Quantitative Association Rule on Fuzzy Clustering with Application to Cross-selling in Telecom Industry

作者：Li Qi^*

来源：2nd International Joint Conference on Computational Sciences and Optimization, 2009-04-24 To 2009-04-26.

DOI：10.1109/CSO.2009.441

• cross-selling
• data mining
• fuzzy clustering
• quantitative association rule

One application of data mining technology is to find the relationship of some product and sell appropriate product to appropriate customer at appropriate time. In order to applying data mining technology to help telecom companies find more cross-selling chances and carry out more available marketing measures to existing customers, an algorithm of quantitative association rule on fuzzy clustering is used in this paper. By combining fuzzy C-means and subtractive cluster method, a fast discrete algorithm can determine some initial clustering centroids avoiding initializing again. We also do some empirical analysis for telecom industry to identifying cross-selling opportunity. Empirical results show that fast discrete algorithm combining FCM and SCM can make association rule index trends differentiation which improves the probability of cross-selling success. The algorithm of quantitative association rule on fuzzy clustering can solve the problem of fasten iterative rate and identify classification of discrete self-adoption, so as to help business department doing exact decision making.

• 出版日期2009
• 单位北京中医药大学