A Comparative Analysis of Clustering Methodology and Application for Market Segmentation: K-Means, SOM and a Two-Level SOM

机译：聚类方法的比较分析及其在市场细分中的应用：K-Means，SOM和两级SOM

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The purpose of our research is to identify the critical variables, to evaluate the performance of variable selection, to evaluate the performance of a two-level SOM and to implement this methodology into Asian online game market segmentation. Conclusively, our results suggest that weight-based variable selection is more useful for market segmentation than full-based and SEM-based variable selection. Additionally, a two-level SOM is more accurate in classification than K-means and SOM. The critical segmentation variables and the characteristics of target customers were different among countries. Therefore, online game companies should develop diverse marketing strategies based on characteristics of their target customers using research framework we propose.

机译：我们的研究目的是确定关键变量，评估变量选择的性能，评估二级SOM的性能，并将这种方法应用于亚洲在线游戏市场细分。总之，我们的结果表明，基于权重的变量选择比基于完全变量和基于SEM的变量选择对市场细分更为有用。此外，两级SOM在分类上比K均值和SOM更准确。不同国家/地区的关键细分变量和目标客户的特征不同。因此，网络游戏公司应使用我们建议的研究框架，根据目标客户的特征来开发多样化的营销策略。

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来源
《Foundations of Intelligent Systems; Lecture Notes in Artificial Intelligence; 4203》|2006年|435-444|共10页
会议地点 Bari(IT)
作者
Sang-Chul Lee; Ja-Chul Gu; Yung-Ho Suh;
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作者单位

Department of Management Information Systems, Korea Christian University, San 204, Hwagok 6-Dong, Kangseo-Ku, Seoul 157- 722, South Korea;

School of Business Administration, Kyung Hee University, 1 Hoegi-Dong, Dongdaemoon-Gu, Seoul 130-701, South Korea;

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正文语种 eng
中图分类人工智能理论;
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A Comparative Analysis of Clustering Methodology and Application for Market Segmentation: K-Means, SOM and a Two-Level SOM

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