Research on Library Big Data Cleaning System based on Big Data Decision Analysis Needs

DOI

10.2991/icmeit-19.2019.62How to use a DOI?

Keywords

University library; Big data decision analysis; Data cleaning and filtering; Data integration application.

Abstract

In the era of big data, university library information management services must be based on actual conditions, using high-quality data to improve big data management. However, high-quality big data is useful data that needs to be filtered and classified. Big data cleansing is an effective way to improve data quality. To this end, the paper proposes to integrate the data resources of efficient libraries, analyze the source and type of useless data, and design a hierarchical management model of data. The model includes management operation level, data cleaning and filtering level, data integration level and big data. At the resource utilization level, after attempting to filter invalid data through data cleaning, the complexity of big data decision analysis is reduced, library big data integration is promoted, big data decision-making is realized, and the possibility of library big data integration and sharing is improved.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jianfeng Liao
AU  - Jianping You
AU  - Qun Zhang
PY  - 2019/04
DA  - 2019/04
TI  - Research on Library Big Data Cleaning System based on Big Data Decision Analysis Needs
BT  - Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SP  - 377
EP  - 382
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.62
DO  - 10.2991/icmeit-19.2019.62
ID  - Liao2019/04
ER  -