数据挖掘算法的改进及其在Chord网络中的应用

摘要

To improve the efficiency of data mining algorithms and the speed of Chord resource location, the paper optimized the data mining algorithm by introducing the conditional model and the depth-first strategy, and then applied the data mining algorithm in the Chord network routing table. The paper speeded up the process of resource location by deleting the routing information of invalid or low frequency use, and adding the relevant routing information. Finally, the performance comparison experiments show that the improved data mining algorithm reflects the superior performance, and effectively improves the positioning performance of the system's resources by mining the association rules of the Chord network.%为了提高数据挖掘算法的效率以及Chord资源定位的速度,引入条件模式以及深度优先的策略改进数据挖掘算法,并将改进后的数据挖掘算法应用到Chord网络的路由表中,通过删除无效或使用频率极低的路由和增加相关路由信息的方法,加速资源定位过程.最终性能比较实验表明,数据挖掘改进算法不仅体现了优越的算法性能,同时通过挖掘Chord网络的关联规则,有效地提升了系统的资源定位性能.