双聚类算法及其在市场分析中的应用

Shuyong Liu, Yan Chen, Mingyuan Yang, Rui Ding
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引用次数: 7

摘要

企业实施产品族架构的前提是对所航行的产品历史数据进行分析,对客户集和产品集进行准确的划分。但是,传统的聚类方法是同时对产品集或客户集进行一次划分。本文回顾了应用最广泛和最成功的双聚类技术,并将双聚类应用于产品集和客户集的同时划分。讨论了双聚类算法。将改进的双聚类算法应用于产品族架构分析的结果表明,与传统聚类方法相比,聚类结果的质量明显提高,挖掘表达式模型更好,在条件下数据具有较强的波动性一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bicluster Algorithm and Used in Market Analysis
The premise of the enterprise that implements the product family architecture is the analysis to the sailed products history data, carrying on accuracy demarcation of the customer sets and products sets. But, the traditional cluster methods consist in simultaneous one partitioning of the set of products or the set of customers. In this paper we review the most widely used and successful biclustering techniques and use bicluster consist in simultaneous partitioning of the set of products and the set of customers. The bicluster algorithm is discussed. The results of the improved bicluster algorithm used in the product family architecture analysis show that, compared with traditional cluster methods, the quality of clustering results is enhanced obviously, the mining expression models are better, and the data possess a strong consistency with fluctuation on the condition.
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