射频识别数据库中封闭多维路径挖掘

• 论文 •

射频识别数据库中封闭多维路径挖掘

陈竹西，杨俊,胡孔法，陈崚，宋爱波

1.扬州大学信息工程学院,江苏扬州225009；2.东南大学计算机科学与工程学院,江苏南京210096

出版日期:2009-10-15 发布日期:2009-10-25

Mining closed multi-dimensional path in radio frequency identification database

CHEN Zhu-xi, YANG Jun, HU Kong-fa, CHEN Ling, SONG Ai-bo

1.College of Information Engineering, Yangzhou University, Yangzhou 225009, China;2.School of Computer Science & Engineering, Southeast University, Nanjing 210096, China

Online:2009-10-15 Published:2009-10-25

摘要/Abstract

摘要： 供应链中的物品具有多个与路径无关的、仅用来表示自身特征的属性维，在挖掘这些移动物品的频繁路径模式时，需要同时考虑到这些属性维。基于高效率的路径模式挖掘算法——封闭路径挖掘，提出了两种多维路径模式挖掘算法，用来解决同一数据库中不同种类的物品移动路径挖掘的问题，并对这些算法的性能进行了分析。经理论分析和实验结果表明，两种算法非常有效。

关键词: 射频识别, 属性维, 多维频繁路径, 封闭频繁路径, 供应链

Abstract: The items in supply chain had path independent attribute dimensions which were only used to express characteristics of the items, it was necessary to consider these attribute dimensions when mining frequency path. To deal with this problem, two multi-dimensional path pattern mining algorithms were proposed based on an effective closed frequency path mining algorithm called Mining Closed Path (MCP), to mine path data for different kinds of items which were stored in same database. Performances of these two algorithms were analyzed. Analytical and experimental results showed that the two algorithms were more efficient than current methods.

Key words: radio frequency identification, attribute dimensions, multi-dimensional frequency path, closed frequency path, supply chain

中图分类号:

TP3111

陈竹西,，杨俊,胡孔法，陈崚，宋爱波. 射频识别数据库中封闭多维路径挖掘[J]. .

CHEN Zhu-xi,, YANG Jun, HU Kong-fa, CHEN Ling, SONG Ai-bo. Mining closed multi-dimensional path in radio frequency identification database[J]. .

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