[1]陈星宇,周展,黄俊文,等.基于关键词挖掘的客户细分方法[J].深圳大学学报理工版,2017,34(3):300-305.[doi:10.3724/SP.J.1249.2017.03300]
　Chen Xingyu,Zhou Zhan,Huang Junwen,et al.A keyword-based mining method for customer segmentation[J].Journal of Shenzhen University Science and Engineering,2017,34(3):300-305.[doi:10.3724/SP.J.1249.2017.03300]
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基于关键词挖掘的客户细分方法()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第34卷
期数:
2017年第3期
页码:
300-305
栏目:
电子与信息科学
出版日期:
2017-05-30

文章信息/Info

Title:
A keyword-based mining method for customer segmentation
文章编号:
201703012
作者:
陈星宇1; 周展1; 黄俊文1; 陶达2
1) 深圳大学管理学院，广东深圳 518060
2) 深圳大学人因工程研究所，广东深圳 518060
Author(s):
Chen Xingyu1;  Zhou Zhan1;  Huang Junwen1;  and Tao Da2
1) College of Management, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
2) Institute of Human Factors and Ergonomics, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
关键词:
人工智能; 自然语言处理; 知识工程; 客户细分; 关键词挖掘; 客户特征; 数据挖掘
Keywords:
artificial intelligence;  natural language processing;  knowledge engineering;  customer segmentation;  keyword mining;  customer characteristics;  data mining
分类号:
TP 311
DOI:
10.3724/SP.J.1249.2017.03300
文献标志码:
A
摘要:
提出一种基于关键词的数据挖掘方法对客户群进行细分，采用自然语义处理的方法从原始客户信息文本中提取客户特征关键词．再通过人工标记一些与内在特征维度相关的关键词，基于这些关键词找到特征客户．最后以特征客户作为训练集，获得更多关于某个维度内客户特征的关键词，再进行新一轮的客户细分．经此模式学习过程，得到基于内在特征维度的客户细分群体．通过与采用随机选择特征关键词的基准化方法进行自动客户细分结果对比，发现采用基于关键词数据挖掘的自动客户细分结果得到的准确度更高，结果更稳健．
Abstract:
We propose a novel customer segmentation method using keyword-based data mining approach. First, keywords about customer characteristics from original customer information are extracted by natural semantic processing. Then, keywords related to intrinsic characteristics are tagged. Based on the keywords, customers with the specific characteristics are identified. Finally, we use the identified customers as the training samples to obtain more keywords about the customer characteristics, and conduct a new round of customer segmentation. After the learning process, customer segmentation groups based on intrinsic characteristics are obtained. Compared with the benchmarking method of random selection of feature keywords for customer segmentation, the feasibility and validity of the proposed method are verified by a case study where a high level of accuracy rate and robustness is observed in the customer segmentation results.

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备注/Memo

备注/Memo:
Received：2016-11-30；Accepted：2017-03-18
Foundation：National Natural Science Foundation of China (71502111)
Corresponding author：Lecturer Tao Da. E-mail: taoda@szu.edu.cn
Citation：Chen Xingyu, Zhou Zhan, Huang Junwen, et al. A keyword-based mining method for customer segmentation［J］. Journal of Shenzhen University Science and Engineering, 2017, 34(3): 300-305.（in Chinese）
基金项目：国家自然科学基金资助项目（71502111）
作者简介：陈星宇 (1983—)，女，深圳大学讲师、博士．研究方向：新产品体验及客户需求管理．E-mail：celine@szu.edu.cn
引文：陈星宇，周展，黄俊文，等．基于关键词挖掘的客户细分方法［J］. 深圳大学学报理工版，2017，34(3)：300-305.
更新日期/Last Update: 2017-04-20