A Scheme for Mining State Association Rules of Process Object Based on Big Data

• 作者: Kai Wang Qiaoyun Song Qingbei Guo Shouning Qu Tao Du Yong Zhang
• 来源期刊: 电脑和通信(英文)
• 学科: 医学
• 关键词: PROCESS OBJECT TIMING ASSOCIATION Chain STATE ASSOCIATION Rule
• 年，卷（期）: dnhtxyw_2014,（14）
• 页码范围: 17-24
• 页数: 8页
• 分类号: R73

摘要

This paper devises a scheme which can discover the state association rules of process object. The scheme aims to dig the hidden close relationships of different links in process object. We adopt a method based on difference and extremum to compute the timing. Clustering is used to classifying the adjusted data, and the next is associating the clusters. Based on the rules of clusters, we produce the rules of links. Association degrees between each two links can be determined. It is easy to get association chains according to the degree. The state association rules that can be obtained in accordance with association rules are the final results. Some industry guidance can be directly summarized from the state association rules, and we can apply the guidance to improve the efficiency of production and operational in allied industries.