摘 要
随着信息技术的迅猛发展，大数据技术逐渐成为推动社会经济变革的重要力量，其在税务管理领域的应用潜力尤为显著。本研究旨在探讨大数据技术在税务信用评价中的应用价值与实践路径，通过构建基于大数据分析的税务信用评价体系，提升税务信用评估的精准性与效率。研究采用文献分析法、案例研究法以及定量分析方法，系统梳理了国内外相关研究成果，并结合实际应用场景设计了一套融合多源数据的税务信用评价模型。该模型以海量税务数据为基础，综合运用机器学习算法和数据挖掘技术，实现了对纳税人信用状况的动态监测与全面评估。研究结果表明，大数据驱动的税务信用评价能够显著提高评估结果的客观性和准确性，同时为税务部门提供决策支持，优化资源配置。此外，本研究创新性地引入了非结构化数据（如社交媒体信息、企业舆情等）作为补充维度，进一步丰富了信用评价指标体系。这一尝试不仅拓展了传统税务信用评价的数据来源，还为个性化税收服务和风险管理提供了新思路。总体而言，本研究的主要贡献在于提出了一种适应新时代需求的税务信用评价框架，为税务管理现代化提供了理论支撑和技术参考，同时也为后续相关研究奠定了基础。
关键词：大数据技术；税务信用评价；机器学习；非结构化数据；资源配置优化
Abstract
With the rapid development of information technology, big data technology has gradually become a crucial force driving socio-economic transformation, with particularly significant application potential in the field of tax administration. This study aims to explore the application value and practical pathways of big data technology in tax credit evaluation by constructing a tax credit evaluation system based on big data analysis, thereby enhancing the accuracy and efficiency of tax credit assessment. Employing literature analysis, case study methods, and quantitative analysis approaches, this research systematically reviews relevant domestic and international studies and designs a tax credit evaluation model that integrates multi-source data based on real-world application scenarios. The model, grounded in massive tax-related datasets, comprehensively applies machine learning algorithms and data mining techniques to achieve dynamic monitoring and comprehensive evaluation of taxpayers' credit conditions. The results indicate that big data-driven tax credit evaluation significantly improves the ob jectivity and precision of assessment outcomes while providing decision support for tax authorities and optimizing resource allocation. Additionally, this study innovatively incorporates unstructured data (e.g., social media information, corporate public sentiment) as supplementary dimensions, further enriching the tax credit evaluation indicator system. This endeavor not only expands the data sources of traditional tax credit evaluation but also offers new insights into personalized tax services and risk management. Overall, the primary contribution of this study lies in proposing a tax credit evaluation fr amework adapted to the needs of the new era, providing theoretical support and technical references for the modernization of tax administration, and laying a foundation for subsequent related research.
Keywords: Big Data Technology; Tax Credit Evaluation; Machine Learning; Unstructured Data; Resource Allocation Optimization
目 录
1绪论 1
1.1税务信用评价与大数据的结合背景 1
1.2大数据在税务信用评价中的意义分析 1
1.3国内外研究现状综述 1
1.4本文研究方法与技术路线 2
2大数据在税务信用评价中的基础理论 2
2.1税务信用评价的基本概念与框架 2
2.2大数据技术的核心原理与应用特点 3
2.3数据驱动的税务信用评价模式构建 3
2.4税务信用评价中大数据的关键作用 4
2.5理论框架对实践的指导意义 4
3大数据在税务信用评价中的关键技术 5
3.1数据采集与预处理方法研究 5
3.2数据挖掘算法在信用评价中的应用 5
3.3机器学习模型的优化与实现 6
3.4数据可视化技术在结果展示中的作用 6
3.5技术难点及解决方案探讨 7
4大数据在税务信用评价中的实践应用 7
4.1实际案例中的大数据应用分析 7
4.2数据驱动的信用评分体系设计 8
4.3风险预警机制的构建与验证 9
4.4政策支持与实施路径探索 9
4.5应用效果评估与改进建议 10
结论 10
参考文献 12
致 谢 13
