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The intelligent management accounting tool proposed in this study, based on the improved K-Means algorithm, effectively improves the efficiency and accuracy of automatic invoice identification. The results show that the recognition accuracy of this tool is 98.63%, which is 5.83% higher than that of Canny algorithm (92.80%), and the average invoice processing speed is 5.34 invoices per second. This means that for a large enterprise that has to process thousands of invoices every day, intelligent management accounting tools can greatly increase the speed of data processing while ensuring high accuracy and can save a lot of labor costs every month. In addition, the tool can also repair the defects of invoice images in real time, adapt to the automatic identification of various types of invoices, and provide a new and efficient solution for enterprise financial data processing. The use of intelligent tools to enhance the ability of enterprises to analyze financial data has fundamentally changed the way financial data is processed.<\/jats:p>","DOI":"10.1177\/14727978251337886","type":"journal-article","created":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T17:27:48Z","timestamp":1745861268000},"page":"4335-4347","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Intelligent management accounting tools based on big data algorithms and invoice automatic recognition algorithms"],"prefix":"10.1177","volume":"25","author":[{"given":"Huizhi","family":"Li","sequence":"first","affiliation":[{"name":"School of Accounting, Guangzhou College of Technology and Business, Guangzhou, China"},{"name":"International Accounting Institute, Philippine Christian University, Manila, Philippine"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3725-3254","authenticated-orcid":false,"given":"Xianghua","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Chemistry and Bio-Engineering, Hunan University of Science and Engineering, Yongzhou, China"},{"name":"Hunan Provincial Engineering Research Center for Ginkgo Biloba, Yongzhou, China"}]}],"member":"179","published-online":{"date-parts":[[2025,4,28]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-189509"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1108\/AAAJ-12-2016-2809"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1108\/QRAM-11-2019-0122"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.26480\/aim.02.2017.13.14"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.26480\/aim.02.2021.58.61"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1504\/IJBEX.2024.139917"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.5267\/j.ac.2020.9.014"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.3934\/mbe.2022391"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2020.07.042"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3172371"},{"issue":"11","key":"e_1_3_3_12_2","first-page":"13094","article-title":"Trocr: transformer-based optical character recognition with pre-trained models","volume":"37","author":"Li M","year":"2023","unstructured":"Li M, Lv T, Chen J, et al. 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