research-article

Research on Tax Inspection Case Selection Model Based on Bayesian Network

Authors:

Qu Ying,

Han Xiaoxin,

Ji WeigeAuthors Info & Claims

IMMS '19: Proceedings of the 2nd International Conference on Information Management and Management Sciences

Pages 198 - 202

https://doi.org/10.1145/3357292.3357329

Published: 23 August 2019 Publication History

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Abstract

Case selection is the first procedure of inspection, and the accuracy of case selection is related to the quality of the whole inspection work.The accuracy of case selection relates to the quality of the whole audit work. Through the selection of financial indicators of enterprises, the Bayesian network method is applied to the field of tax inspection and case selection. With the help of the reasoning function of the network, the probability of occurrence is predicted, and a case selection model is established to reflect the uncertainty and complexity of the case selection system, so as to realize the prediction and diagnosis of the case selection system. Taking the honesty state of the selected enterprise as a probability event, the accuracy of this model is 93.3%. It shows that the model can not only improve the accuracy of tax audit case selection, but also provide the method guidance and decision-making reference for tax audit case selection.

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Cited By

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Zuccaro CPlaisent MBernard P(2021)A Preliminary Framework to Fight Tax Evasion in the Home Renovation MarketIntelligent Analytics With Advanced Multi-Industry Applications10.4018/978-1-7998-4963-6.ch015(304-325)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-4963-6.ch015

Index Terms

Research on Tax Inspection Case Selection Model Based on Bayesian Network
1. General and reference
  1. Cross-computing tools and techniques
    1. Evaluation
    2. Metrics
2. Information systems
  1. Data management systems
    1. Database management system engines
      1. DBMS engine architectures
  2. Information systems applications
    1. Mobile information processing systems

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IMMS '19: Proceedings of the 2nd International Conference on Information Management and Management Sciences

August 2019

227 pages

ISBN:9781450371445

DOI:10.1145/3357292

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Guilin: Guilin University of Technology, Guilin, China
Southwest Jiaotong University

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Association for Computing Machinery

New York, NY, United States

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Published: 23 August 2019

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IMMS 2019: 2019 2nd International Conference on Information Management and Management Sciences

August 23 - 25, 2019

Chengdu, China

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Zuccaro CPlaisent MBernard P(2021)A Preliminary Framework to Fight Tax Evasion in the Home Renovation MarketIntelligent Analytics With Advanced Multi-Industry Applications10.4018/978-1-7998-4963-6.ch015(304-325)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-4963-6.ch015

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Recommendations

The Research of Tax Inspection Based-On Generalized Regression Neural Network

Application of Bayesian Network for Nikkei Stock Return Prediction

Using Bayesian network and AIS to perform feature subset selection

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