Abstract
The paper presents a novel approach for customer segmentation which is the basic issue for an effective CRM (Customer Relationship Management). Firstly, the chi-square statistical analysis is applied to choose set of attributes and K-means algorithm is employed to quantize the value of each attribute. Then DBSCAN algorithm based on density is introduced to classify the customers into three groups (the first, the second and the third class). Finally biclustering based on FP-tree algorithm is used in the three groups to obtain more detailed information. Experimental results on the dataset of an airline company show that the biclustering could segment the customers more accurately and meticulously. Compared with biclustering based on Apriori, the Fp-tree is more efficient on the large dataset.
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Hu, X. et al. (2014). A Novel Approach for Customer Segmentation Based on Biclustering. In: Huang, Z., Liu, C., He, J., Huang, G. (eds) Web Information Systems Engineering – WISE 2013 Workshops. WISE 2013. Lecture Notes in Computer Science, vol 8182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54370-8_26
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DOI: https://doi.org/10.1007/978-3-642-54370-8_26
Publisher Name: Springer, Berlin, Heidelberg
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