Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)

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Algorithm Analysis of Public Service Accessibility

Authors
Ying Sun1, *
1Institute of Governance, Party School of Liaoning Provincial Party Committee, Shenyang, People’s Republic of China
*Corresponding author. Email: 12017366@qq.com
Corresponding Author
Ying Sun
Available Online 12 December 2022.
DOI
10.2991/978-94-6463-024-4_60How to use a DOI?
Keywords
Public service; Accessibility; Algorithm analysis; Deep learning
Abstract

In order to maximize the value of various public service data resources under certain computing resources, it is necessary to develop public service algorithms for various application scenarios of public services, so as to realize intelligent computing and service engine from various public service data to corresponding scenario applications. The public service algorithm center is similar to the algorithm “shelf”, which has the characteristics of modular and plug-in deployment. It can be called by scenario application development in the form of API interface or dynamic library (.Lib). It can not only run on the cloud computing platform, but also be deployed to other business systems. It also can connect existing resources, including basic platforms, business systems, data center or other development tools. Each algorithm module can also be interconnected to form a new integrated algorithm. In the future, combined with the accumulation of large-scale public service algorithms and public service knowledge map resources, based on the deep learning and automatic algorithm generation ability, a new generation of self-generating brain core of multimodal algorithms facing new scene problems can be formed, and at the same time, the limited precise call scheduling of computing quantity and the limited precise borrowing of computing power can be realized.

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.

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Volume Title
Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
12 December 2022
ISBN
10.2991/978-94-6463-024-4_60
ISSN
2589-4900
DOI
10.2991/978-94-6463-024-4_60How 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

risenwbib
TY  - CONF
AU  - Ying Sun
PY  - 2022
DA  - 2022/12/12
TI  - Algorithm Analysis of Public Service Accessibility
BT  - Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
PB  - Atlantis Press
SP  - 574
EP  - 587
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-024-4_60
DO  - 10.2991/978-94-6463-024-4_60
ID  - Sun2022
ER  -