摘要
本文应用数据挖掘技术对市场细分的研究包括:如何利用SOM聚类技术解决市场细分问题;如何将SOM聚类的市场细分结构结果可视地呈现给市场决策人员的问题。这两部分研究整合为企业市场战略集成一个研究途径,包括:偏好数据的收集与前处理步骤、偏好数据聚类步骤、偏好数据的可视化步骤。实验结果表明,本文提出的研究途径成功发现了人工数据集中预设的聚类模式,与通常研究途径相比具有明显的优点。在实际市场数据分析中,获得了与事实相符的结论并提供了有价值的决策支持信息。
The research in market segmentation includes two main parts. We focus firstly on discussing the market segmentation problem by applying SOM clustering technique in data mining discipline. The second part is focus on displaying market segmentation structure. We apply visualization technique to represent the market structure clearly in a two dimensional plane so that the marketers can make their market strategies easier. The two main parts are organized as an integrated approach. Such an approach includes three core steps： preference data collecting step, preference data clustering step by SOM neural networks and visualization step by ideal point model. The experirnents show that the approach yields meaningful results and is comparable and complementary to the most general ones.
出处
《计算机科学》
CSCD
北大核心
2005年第12期98-100,共3页
Computer Science
关键词
偏好序列
聚类
市场细分
自组织特征映射
Preference order, Cluster analysis, Market segmentation, SOM
