E-Loyalty Simulation Based on Hidden Markov Model
With the rapid development of E-retailing business, customer loyalty management becomes more important to E-retailers. However, E-loyalty is not observable from the perspective of merchants, there should have data mining before recognizing and grouping consumers. Moreover, the evolution process of customer loyalty shows dynamic, stochastic and non-after-effect characteristics, which can be called as a Markov process. The paper explores how Hidden Markov model can be applied on E-loyalty researches. Combining with K-mean clustering method, this paper builds the HMM-based E-loyalty simulation model, including transition matrix of customer loyalty and transaction behavior. Detailed experimental results are given in the last part.
KeywordsHidden Markov model Customer E-loyalty K-means clustering Electronic Commerce
This paper is sponsored by the Bilingual Course Foundation of Chongqing Normal University.
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