Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)

Optimization Analysis of Public Policy Online Voting System Based on Data Mining Algorithm

Authors
Haisheng Hu1, Dong Chen2, *
1School of Public Policy, Chiang Mai University, Chiangmai, 502000, Thailand
2Nanyang Technological University SINGAPORE, 50 Nanyang Avenue, Singapore, 637121, Singapore
*Corresponding author. Email: CHEN1532@e.ntu.edu.sg
Corresponding Author
Dong Chen
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-064-0_43How to use a DOI?
Keywords
Data Mining Algorithm; Association Rule Algorithm; Public Policy; Online Voting
Abstract

Correct decision-making and effective implementation of public policies will bring positive results to the development of the economy and the advancement of society. Errors in decision-making or improper implementation will bring certain negative effects. In a sense, the issue of public policy is the most important issue of a country's legislation and judiciary, and it is also the main method used by the authorities to safeguard the interests of the people. With the development of the Internet, a lot of information can be effectively processed through computer network technology, so information feedback has become the goal that people pursue, and the online voting system is one of the products. In this paper, a network online voting system is specially designed for public policy formulation and decision-making. The association rules algorithm in the data mining algorithm is introduced, and the system can exclude the user IPs who voted repeatedly. Through the algorithm statistical data results, the voting rate and voting items can be found. The algorithm also optimizes the statistical process of voting results, making voting data processing more convenient and accurate. After the system is tested, the operational reliability of the system in this paper is also verified.

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.

Download article (PDF)

Volume Title
Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-064-0_43
ISSN
2589-4900
DOI
10.2991/978-94-6463-064-0_43How to use a DOI?
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  - Haisheng Hu
AU  - Dong Chen
PY  - 2022
DA  - 2022/12/27
TI  - Optimization Analysis of Public Policy Online Voting System Based on Data Mining Algorithm
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 402
EP  - 409
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_43
DO  - 10.2991/978-94-6463-064-0_43
ID  - Hu2022
ER  -