Application of Robotic Process Automation Combined with Chinese Grammatical Error Detection
Authors: 
Kai Liu, Yutao Yang, Minhang Li, Jia Yang, Yuchao Li, Dazhu Yan, Wenxin Liu, Weiyang He, Wenhong TianAuthors Info & Claims
Article No.: 17, Pages 1 - 6
Abstract
Automation applications have become one of the emerging trends in machine intelligence. In traditional automation applications, almost all operations are based on programming, scripts or Application Programming Interfaces. However, the continuous development of business and change of processes amplify some disadvantages of traditional automation technology. Robotic Process Automation (RPA), a software robot adopted as a new automation technology to improve the efficiency and productivity of enterprises, can imitate human behavior. RPA tools are used to design and deploy these software robots, which use predefined activities and business rules to perform the combination of tasks, transactions and processes across software systems. Integrating grammatical error detection, RPA has better performance in specific business than ordinary RPA. This is because RPA is able to identify grammar errors that are not easy to detect so as to greatly improve the efficiency.
References
[1]
Julia, S. 2020. Robotic process automation — a driver of digital transformation?. Engineering Management in Production and Services, 12.
[2]
Diwan G, Goguen T A. ARTIFICIAL INTELLIGENCE AND ROBOTIC PROCESS AUTOMATION FOR AUTOMATED DATA MANAGEMENT:, US20190180746A1[P]. 2019.
[3]
Mohammed A. Shehab, Yahya M. Tashtoush, Wegdan A. Hussien, Mohammed N. Alandoli, and Yaser Jararweh, "An Accumulated Cognitive Approach to Measure Software Complexity," Vol. 6, No. 1, pp. 27-33, February, 2015.
[4]
Fu R, Pei Z, Gong J, Chinese grammatical error diagnosis using statistical and prior knowledge driven features with probabilistic ensemble enhancement[C]. The 5th Workshop on Natural Language Processing Techniques for Educational Applications, Melbourne, Australia. 2018: 52-59 Jon M. Kleinberg. 1999. Authoritative sources in a hyperlinked environment. J. ACM 46, 5 (September 1999), 604–632. https://doi.org/10.1145/324133.324140
[5]
Ren H, Yang L, Xun E. A sequence to sequence learning for Chinese grammatical error correction[C]. CCF International Conference on Natural Language Processing and Chinese Computing, Hohhot, China. 2018: 401-410. James W. Demmel, Yozo Hida, William Kahan, Xiaoye S. Li, Soni Mukherjee, and Jason Riedy. 2005. Error Bounds from Extra Precise Iterative Refinement. Technical Report No. UCB/CSD-04-1344. University of California, Berkeley.
[6]
Li S, Zhao J, Shi G, Chinese grammatical error correction based on convolutional sequence to sequence model[J]. IEEE Access, 2019, 7: 72905-72913.Jason Jerald. 2015. The VR Book: Human-Centered Design for Virtual Reality. Association for Computing Machinery and Morgan & Claypool.
[7]
Wang S, Wang B, Gong J, Combining ResNet and Transformer for Chinese grammatical error diagnosis[C]. The 6th Workshop on Natural Language Processing Techniques for Educational Applications, Suzhou, China. 2020: 36-43.R Core Team. 2019. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
[8]
Luo Y, Bao Z, Li C, Chinese grammatical error diagnosis with graph convolution network and multi-task learning[C]. The 6th Workshop on Natural Language Processing Techniques for Educational Applications, Suzhou, China. 2020: 44-48. John R. Smith and Shih-Fu Chang. 1997. VisualSEEk: a fully automated content-based image query system. In Proceedings of the fourth ACM international conference on Multimedia (MULTIMEDIA ’96). Association for Computing Machinery, New York, NY, USA, 87–98. https://doi.org/10.1145/244130.244151
[9]
Cao Y, He L, Ridley R, Integrating BERT and score-based feature gates for Chinese grammatical error diagnosis[C]. The 6th Workshop on Natural Language Processing Techniques for Educational Applications, Suzhou, China. 2020: 49-56.Alper Yilmaz, Omar Javed, and Mubarak Shah. 2006. Object tracking: A survey. ACM Comput. Surv. 38, 4 (December 2006), 13–es. https://doi.org/10.1145/1177352.1177355
[10]
S H, Wang J. CYUT team Chinese grammatical error diagnosis system report in NLPTEA2020 CGED shared task[C]. The 6th Workshop on Natural Language Processing Techniques for Educational Applications, Suzhou, China. 2020: 91-96.
[11]
Liu Y, Ott M, Goyal N, Roberta: A robustly optimized bert pretraining approach[J]. arXiv preprint arXiv:1907.11692, 2019.
[12]
Strubell E, Verga P, Belanger D, Fast and accurate entity recognition with iterated dilated convolutions[J]. arXiv preprint arXiv:1702.02098, 2017.
[13]
Han Y, Yan Y, Han Y, Chinese grammatical error diagnosis based on RoBERTa-BiLSTMCRF model[C]. The 6th Workshop on Natural Language Processing Techniques for Educational Applications, Hohhot, China. 2020: 97-101.
[14]
Zhao Y, Jiang N, Sun W, Overview of the nlpcc 2018 shared task: grammatical error correction[C]. CCF International Conference on Natural Language Processing and Chinese Computing, Hohhot, China. 2018: 439-445.
[15]
Wang S, Wang B, Gong J, Combining ResNet and Transformer for Chinese grammatical error diagnosis[C]. The 6th Workshop on Natural Language Processing Techniques for Educational Applications, Suzhou, China. 2020: 36-43.
[16]
Fang M, Fu K, Wang J, A hybrid system for NLPTEA-2020 CGED shared task[C]. The 6th Workshop on Natural Language Processing Techniques for Educational Applications, Hohhot, China. 2020: 67-77.
[17]
Hsin-Ke Lu, Peng-Chun Lin, Pin-Chia Huang, and An Yuan, "Deployment and Evaluation of a Continues Integration Process in Agile Development," Vol. 8, No. 4, pp. 204-209, November, 2017.
[18]
Chadatarn Raksawat and Pattama Charoenporn, "Software Testing System Development Based on ISO 29119," Journal of Advances in Information Technology, Vol. 12, No. 2, pp. 128-134, May 2021.
Index Terms
- Application of Robotic Process Automation Combined with Chinese Grammatical Error Detection
Recommendations
Improvement of the LR parsing table and its application to grammatical error correction
A LR parsing table is generally made use of the parsing process based on the context free grammar for natural languages. Besides the parsing process, it can be used as the index of approximate pattern matching and error correction, because it has the ...
A rule‐based method to effectively adopt robotic process automation
AbstractRobotic Process Automation (RPA) is an emerging software technology for automating business processes. RPA uses software robots to perform repetitive and error‐prone tasks previously done by human actors quickly and accurately. These robots ...
image image
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
September 2022
132 pages
ISBN:9781450397407
DOI:10.1145/3564982
Copyright © 2022 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 30 January 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- ??????????????????????Typical application of research on digital transformation technology of tobacco business in Yunnan Province?
Conference
ICACS 2022
ICACS 2022: 2022 The 6th International Conference on Algorithms, Computing and Systems
September 16 - 18, 2022
Larissa, Greece
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 55Total Downloads
- Downloads (Last 12 months)21
- Downloads (Last 6 weeks)2
Reflects downloads up to 23 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format