Lei WangGüzin MayzusMayzus, GüzinWang, LeiS. Sun , P. Yu , J. Zou , T. Hong2025-10-0620229789819680023, 9789819658473, 9789819600571, 9789819644292, 9789819637577, 9783319030135, 9783642363283, 9789819648115, 9783642384653, 9789819920914978981194774218761119, 187611001876-110010.1007/978-981-19-4775-9_592-s2.0-85141717298https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141717298&doi=10.1007%2F978-981-19-4775-9_59&partnerID=40&md5=5997b785f853e8a59808a110bb59aadehttps://gcris.yasar.edu.tr/handle/123456789/8784https://doi.org/10.1007/978-981-19-4775-9_59With the advent of the era of big data there has been a call to identify data resources as assets and enter the enterprise balance sheet accounting. However there are still different opinions about whether data resources should be recognized as assets. No matter whether the existing research advocates identifying data resources as assets or not its research methods are usually normative studies based on the logic basis of accounting standards but lack of methods to guide the practice. This paper focuses on the accounting recognition of data assets and combines the essential characteristics of big data to build a model based on Naive Bayes method which can assist enterprises to carry out the accounting recognition of data assets. © 2022 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessAccounting Confirmation, Assets, Data Resources, Information Technology, Naive Bayes, Classifiers, Computation Theory, Accounting Confirmation, Accounting Standards, Asset, Balance Sheets, Data Assets, Data Resources, Model Construction, Naive Bayes, Naive-bayes Algorithm, Research Method, Big DataClassifiers, Computation theory, Accounting confirmation, Accounting standards, Asset, Balance sheets, Data assets, Data resources, Model construction, Naive bayes, Naive-Bayes algorithm, Research method, Big dataAccounting ConfirmationAssetsInformation TechnologyNaive BayesData ResourcesConference Object