Research Article
Anomaly Monitoring System of Enterprise Financial and Economic Information Based on Entropy Clustering
@INPROCEEDINGS{10.1007/978-3-031-28787-9_17, author={Yu Chen and Kaili Wang}, title={Anomaly Monitoring System of Enterprise Financial and Economic Information Based on Entropy Clustering}, proceedings={Advanced Hybrid Information Processing. 6th EAI International Conference, ADHIP 2022, Changsha, China, September 29-30, 2022, Proceedings, Part I}, proceedings_a={ADHIP}, year={2023}, month={3}, keywords={Entropy clustering Corporate financial economy Information anomaly Monitoring system Data cleaning k-means}, doi={10.1007/978-3-031-28787-9_17} }- Yu Chen
Kaili Wang
Year: 2023
Anomaly Monitoring System of Enterprise Financial and Economic Information Based on Entropy Clustering
ADHIP
Springer
DOI: 10.1007/978-3-031-28787-9_17
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.
