Abstract
The currently used information anomaly monitoring system has problems of low accuracy and efficiency. In this regard, an abnormal monitoring system of enterprise financial and economic information based on entropy clustering is designed. On the basis of the design of the hardware and control module of the economic information abnormal monitoring system; the crawler tool is used to collect the financial and economic information of the enterprise; the collected data information is cleaned by the mapping operation; the processed data is processed by the abnormal knowledge discovery principle. In feature extraction, abnormal information features are obtained through decision tree; the abnormal information monitoring is realized by using the k-means algorithm of information entropy. The experimental results show that the designed system has an average alarm correct rate of 92.55% and a short response time, which is of practical value.
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Jiangsu Province “14th Five-Year” Business Administration Key Construction Discipline Project (SJYH2022-2/285).
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Chen, Y., Wang, K. (2023). Anomaly Monitoring System of Enterprise Financial and Economic Information Based on Entropy Clustering. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-28787-9_17
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DOI: https://doi.org/10.1007/978-3-031-28787-9_17
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