Design and Application of Modern Big Data Technology in College Entrance Examination
- DOI
- 10.2991/978-94-6463-002-2_12How to use a DOI?
- Keywords
- College entrance examination; Application system; Database; Big data technology; Design and application
- Abstract
In recent years, with the implementation of new reform of the college entrance examination policy, and the rapid development of computer information technology, the college entrance examination application has become a hot topic, especially in the parallel college application process, which the candidates should fill in the application form according to their own scores and the lowest score of universities and colleges. At present, the most commonly used method is to make use of big data to effectively analyze the influencing factors and improve the admission probability, and to provide more scientific and convenient choices for the majority of candidates. It can be seen that big data analysis plays a vital role in the proposing process. This thesis introduces the steps and methods of big data processing, to collect, study and analyze data by data mining technology and database technology, providing reference information and data support for college entrance examination application.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Haidong Yang PY - 2022 DA - 2022/11/10 TI - Design and Application of Modern Big Data Technology in College Entrance Examination BT - Proceedings of the 2nd International Conference on Artificial Intelligence and Cloud Computing (ICAICC 2022) PB - Atlantis Press SP - 88 EP - 94 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-002-2_12 DO - 10.2991/978-94-6463-002-2_12 ID - Yang2022 ER -