Routing attribute data mining based on rough set theory

被引：0

作者：

Liu, YB ^{[1
]}

Tang, H

Wang, MH

Sun, SX

机构：

[1] UEST China, Sch Comp Sci, Chengdu 610010, Peoples R China

[2] Chongqing Univ Posts & Telecommun, Chongqing 400065, Peoples R China

来源：

ADVANCED DATA MINING AND APPLICATIONS, PROCEEDINGS | 2005年 / 3584卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

QOSPF (Quality of Service Open Shortest Path First) based on QoS routing has been recognized as a missing piece in the evolution of QoS-based service offerings in the Internet. A data mining method for QoS routing based on rough set theory has been presented in this paper. The information system about the link is created from the subnet, and the method of rough set can mine the best route from enormous irregular link QoS data and can classify the link with the link-status data. An instance applying to the theory is presented, which verifies the feasibility that the most excellent attribute set is mined by rough set theory for compatible data table.

引用

页码：276 / 283

页数：8

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