摘 要
随着信息技术的迅猛发展，大数据技术在各领域的应用日益广泛，税务审计作为维护税收秩序和保障国家财政收入的重要手段，也亟需借助大数据技术提升效率与精准度。本研究旨在探讨大数据技术在税务审计中的数据挖掘与分析方法，以解决传统审计模式中信息处理能力不足、异常检测效率低下等问题。研究采用数据挖掘算法与机器学习模型相结合的方式，对海量税务数据进行多维度分析，包括特征提取、模式识别及风险评估等关键环节。通过构建基于大数据的税务审计分析框架，实现了对企业税务行为的实时监控与智能化评估。实验结果表明，该方法能够显著提高税务异常检测的准确率，并有效降低误报率，为税务审计工作提供了科学依据和技术支持。此外，本研究创新性地引入了深度学习技术优化风险预测模型，进一步提升了系统的适应性和鲁棒性。总体而言，本研究不仅为税务审计领域提供了新的技术路径，还为大数据技术在其他监管场景中的应用积累了宝贵经验，具有重要的理论价值和实践意义。
关键词：大数据技术；税务审计；数据挖掘；机器学习；风险评估
Abstract
With the rapid development of information technology, big data technology is increasingly being applied across various fields. As an important means to maintain tax order and ensure national fiscal revenue, tax auditing urgently needs to leverage big data technology to enhance its efficiency and accuracy. This study aims to explore data mining and analytical methods of big data technology in tax auditing, addressing issues such as insufficient information processing capabilities and low efficiency in anomaly detection within traditional auditing models. By integrating data mining algorithms with machine learning models, this research conducts multi-dimensional analyses of massive tax datasets, focusing on key processes such as feature extraction, pattern recognition, and risk assessment. A big data-based tax auditing analytical fr amework was constructed, enabling real-time monitoring and intelligent evaluation of corporate tax behaviors. Experimental results demonstrate that this approach significantly improves the accuracy of tax anomaly detection while effectively reducing false alarm rates, providing scientific evidence and technical support for tax auditing operations. Additionally, this study innovatively incorporates deep learning techniques to optimize the risk prediction model, further enhancing the system's adaptability and robustness. Overall, this research not only offers new technological pathways for the field of tax auditing but also accumulates valuable experience for the application of big data technology in other regulatory scenarios, possessing significant theoretical value and practical implications.
Keywords: Big Data Technology; Tax Audit; Data Mining; Machine Learning; Risk Assessment
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状分析 1
1.3本文研究方法与技术路线 2
2大数据在税务审计中的基础理论 2
2.1税务审计的基本概念与流程 2
2.2大数据技术的核心原理 3
2.3数据挖掘在税务审计中的作用 3
2.4大数据分析方法的适用性探讨 4
2.5理论框架构建 4
3数据挖掘技术在税务审计中的应用实践 5
3.1数据采集与预处理策略 5
3.2常见数据挖掘算法的应用场景 5
3.3异常检测在税务审计中的实现 6
3.4风险评估模型的设计与优化 6
3.5实践案例分析 7
4大数据分析对税务审计效率的影响研究 7
4.1提高审计效率的关键因素 7
4.2数据驱动的审计决策支持系统 8
4.3审计资源分配的优化方案 8
4.4数据分析结果的可视化呈现 9
4.5效率提升的实际效果评估 9
结论 10
参考文献 11
致 谢 12
