Design of Data Standardization Cleaning System Under Multi-source Data Access

被引：1

作者：

Li, Bo ^{[1
]}

Zhao, Ruifeng ^{[2
]}

Chen, Fengchao ^{[3
]}

Zhang, Bo ^{[1
]}

Zhou, Lide ^{[3
]}

He, Yipeng ^{[3
]}

Lu, Chengbo ^{[3
]}

机构：

[1] South China Univ Technol, Sch Elect Power, Guangzhou 510640, Guangdong, Peoples R China

[2] Power Dispatching & Control Ctr Guangdong Grid Co, Guangzhou 510600, Guangdong, Peoples R China

[3] Guangdong Power Grid Corp, Dongguan Power Supply Bur, Dongguan 523008, Guangdong, Peoples R China

来源：

FORTHCOMING NETWORKS AND SUSTAINABILITY IN THE IOT ERA (FONES-IOT 2021), VOL 2 | 2022年 / 130卷

关键词：

Multi source data; Multi task optimization; Data cleaning; Massive data;

D O I：

10.1007/978-3-030-99581-2_7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Due to the poor initial clustering ability of data, the processing time of data standardization cleaning system for multi-source data is increasing. To solve this problem, the data standardization cleaning system with multi-source data access is designed. According to the characteristics of multi-source data, the preliminary clustering module is set to complete the data preprocessing. The data similarity is calculated to determine whether the data to be processed or not need to be cleaned. The traditional system data cleaning technology is used to process the data to complete the multi-source data cleaning. So far, the design of data standardization cleaning system under multi-source data access has been completed. The experimental results show that the speed of data missing value processing, the effect of data screening and data standardization processing are better, and the comprehensive performance of system data cleaning is better. Therefore, this system is more suitable for multi-source data processing.

引用

页码：59 / 67

页数：9

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