基于混沌稳定子控机制的微博社区数据挖掘算法  

Microblog community data mining algorithm based on chaotic stability sub-control mechanism

作　　者：梁娟[1] Liang Juan(Shaanxi College of Communication Technology, Xi＇an 710018, China)

机构地区：[1]陕西交通职业技术学院

出　　处：《国外电子测量技术》2018年第4期30-33,共4页Foreign Electronic Measurement Technology

摘　　要：当前微博社区数据存在稳定挖掘算法的挖掘效率较低、鲁棒性能不佳等难题,提出了一种基于混沌稳定子控机制的微博社区数据稳定挖掘算法。首先,利用微博社区数据存在的混沌特性进行挖掘架构的构建,将处于混沌稳定特征状态的微博数据进行匹配分割;随后,基于微博数据分段特征的不同,将不同状态的混沌稳定流进行成本核算,改善了算法在复杂条件成本核算困难的问题。最后,根据核算过程中不同混沌稳定流所存在的数字特征,对全部的数据进行整体挖掘成本核算,进一步降低了核算过程中的复杂度,改善了挖掘算法的数据挖掘效率。仿真实验表明,与自映射一体化挖掘算法（self mapping mining algorithm,SMM算法）相比,该算法的数据挖掘性能及适用范围有了明显的提高,具有良好的实践应用价值。In order to solve the problems of low efficiency,low performance and poor transaction process in the current microblogging community data stabilization mining algorithm,a microblogging community data stabilization mining algorithm based on chaos stable sub-control mechanism is proposed.The construction of the mining structure is carried out by using the chaotic characteristics of the microblogging community data.The chaotic steady flow arriving at the asynchronous arrival is matched.Then,the chaotic steady flow of different states is calculated based on the difference of the segment features.Difficulty of complex conditional costing.According to the digital characteristics of different chaotic steady flow in the accounting process,the whole mining cost is calculated for the whole data,which further reduces the complexity of the accounting process and improves the data mining efficiency of the mining algorithm.Simulation results show that compared with the traditional self-mapping mining algorithm（SMM algorithm）,the data mining performance and application scope of this algorithm have been improved obviously and it has good practical application value.

关 键 词：微博社区 数据挖掘 混沌稳定流 混沌特性 核算递归 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TN92[自动化与计算机技术—计算机科学与技术]