摘要
对终端用户信息的快速获取,能够有效提高大数据下用户信息处理效率。对大数据分析下终端用户信息获取,需要建立用户信息的数据预处理模型,去除终端用户信息中存在的噪声,完成用户信息的快速获取。传统方法对下近似的计算方法进行了重新定义,并对快速获取模型进行探讨,但忽略了对用户信息中噪声的滤除,导致信息获取效率偏低。提出终端用户信息快速获取方法。根据科尔莫戈罗夫多项式建立用户信息的数据预处理模型,去除终端用户信息中存在的噪声,提高快速获取结果的准确性,采用贝叶斯定理计算终端用户信息的特征,根据信息特征快速的完成获取,提高了方法的获取效率。仿真证明,上述方法可以在较短的时间内准确的完成终端用户信息的快速获取。
The efficiency of user information processing in big data can be effectively improved by the rapid acqui- sition of terminal users＇ information. In order to obtain the information of terminal user in big data, the data prepro- eessing model of user information is established to remove the noise in terminal user information, and complete the rapid acquisition of user information. In the traditional method, the filtering of noise in user information is ignored, which results in low efficiency of information acquisition. In this paper, the rapid acquisition method of terminal user information is proposed. According to Kolmogorov polymerization, data preprocessing model of user information is es- tablished to remove the noise existing in user information terminal. Then, the accuracy of rapid acquisition is im- proved. Moreover, Bayes theorem is used to calculate features of terminal user information. On the basis of informa- tion feature, acquisition is completed quickly and the acquisition efficiency of method is improved. Simulation results show that the proposed method can achieve the rapid acquisition of terminal user information in a short time.
出处
《计算机仿真》
北大核心
2018年第2期441-445,共5页
Computer Simulation
基金
山西省自然科学基金(201601D011042)
关键词
大数据
终端用户
快速获取
Big data
Terminal user
Rapid acquisition
