使用支持向量机模型实现RFM分析

Q3 Medicine Koomesh Pub Date : 2018-08-01 DOI:10.1109/I-SMAC.2018.8653758
Ananthi Sheshasaayee, L. Logeshwari
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引用次数: 0

摘要

在现代商业中,客户响应是服务的重要特征之一。客户关系管理准确地预测了宝贵的客户。因为需要注意评价低反应等级的客户。直销部门大多是随机选择,降低影响程度的问题。但在线营销部门在识别客户反应方面面临更多困难。本文提出了基于RFM值的支持向量机模型,并根据货币值来预测最近权和频率权。
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IMPLEMENTATION OF RFM ANALYSIS USING SUPPORT VECTOR MACHINE MODEL
In the modern business customer response is one of the vital characteristics of services. The customer relationship management accurately predict the invaluable customer. Because attention is needed to rate low response rating customers. Most of the direct marketing sectors randomly select and reduce degree of the influencing problem. But online marketing sectors face more difficulties to identify customer responses. This paper proposes SVM model based on the RFM values and also according to the monetary value to predict recency and frequency weights.
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来源期刊
Koomesh
Koomesh Medicine-Medicine (all)
CiteScore
0.80
自引率
0.00%
发文量
0
审稿时长
24 weeks
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