Trend analysis of product function using sequential pattern mining

被引：0
|
作者：
Yu, Li [1 ]
Zhang, Zaifang [1 ]
机构：
[1] Shanghai Univ Finance & Econ, Shanghai Key Lab Financial Informat Technol, 777 Guoding Rd, Shanghai 200433, Peoples R China
来源：
COMPUTER AND INFORMATION TECHNOLOGY | 2014年 / 519-520卷
基金：
上海市自然科学基金; 中国国家自然科学基金;
关键词：
Product function; Sequential pattern mining; AprioriAll; Mass customization;
D O I：
10.4028/www.scientific.net/AMM.519-520.736
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
During the early stage of product design, it is important for design engineers to decide the most appropriate functions for various customers. To facilitate this time consuming task, sequential pattern mining is applied to uncover the useful patterns in historical database. The mined sequential patterns can reflect the dynamic change of product functions, which can help design engineers find the most suitable product functions for customers. Based on the historical sales transactions of computer, a case study is conducted to illustrate the proposed method.
引用
收藏
页码：736 / +
页数：2
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