Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/106134
Title: | Banking system incidents analysis using knowledge graph | Authors: | Kang, WH Cheung, CF |
Issue Date: | 2023 | Source: | International journal of knowledge and systems science, 2023, v. 14, no. 1, p. 1-23 | Abstract: | Risk incidents in the banks' systems have caused significant social impacts and economic losses. This study proposes a risk incident knowledge modeling and analysis approach based on the knowledge graphs to realize the effective integration and continuous accumulation of incident knowledge. The authors are the first to analyze the advantages of knowledge graphs in risk incident knowledge integration for the bank's core system. Moreover, they study and compare the related field's state-ofthe-art models (including CRF, BiLSTM, BiLSTM-CRF, BERT-BiLSTM-CRF). This paper proposes an improved Bert-BiLSTM-CRF model to perform entity recognition which replaces "individual word mask and training" with "full word mask and training" targeted to solve the problem of low accuracy in the extraction of incident text entities in the banking system. Experiments on 1000 banking system incident material show that the improved Bert-BiLSTM-CRF model outperforms the state-of-the-art models based on the comparison of recall (R), precision (P), and F1-measure, with a 2%-9% improvement in the F1-measure. | Keywords: | Banking System Incident Analysis Knowledge Graph Knowledge Management Name Entity Recognition |
Publisher: | IGI Global | Journal: | International journal of knowledge and systems science | ISSN: | 1947-8208 | EISSN: | 1947-8216 | DOI: | 10.4018/IJKSS.325794 | Rights: | This article published as an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and production in any medium, provided the author of the original work and original publication source are properly credited. The following publication Kang, W. & Cheung, C. F. (2023). Banking System Incidents Analysis Using Knowledge Graph. International Journal of Knowledge and Systems Science (IJKSS), 14(1), 1-23 is available at https://dx.doi.org/10.4018/IJKSS.325794. |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Kang_Banking_System_Incidents.pdf | 947.84 kB | Adobe PDF | View/Open |
Page views
15
Citations as of Jun 30, 2024
Downloads
3
Citations as of Jun 30, 2024
![](/image/google_scholar.jpg)
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.