摘要
随着税收优惠政策数量的迅速增加,纳税人面对海量的税收优惠政策难以快速定位与自身相关的优惠内容,导致许多纳税人没有享受到应该享受的优惠政策。基于预训练语言模型BERT与规则处理相结合的方法实现了对税收优惠政策法规的表示、关键要素抽取和税收优惠的可视化查询,使纳税人可以快速准确地定位与自身相关的税收优惠信息,并对结果进行可视化展示。实验结果表明,关键要素抽取性能优越,税收优惠政策查询快速直观,可有效缓解海量税收优惠信息过载。
With the rapid increase in the number of preferential tax policies,taxpayers face a large number of preferential tax policies,and it is difficult for taxpayers to quickly locate the preferential content related to them.As a result,many taxpayers do not enjoy the preferential policies they should enjoy.Based on the combination of pre-training language model BERT and rule processing,the visualization was realized of the characterization of preferential tax policies and regulations,the extraction of key elements,and the visual query of tax incentives,so that taxpayers can intuitively and quickly locate tax incentives related to themselves,and visualize the results.The experimental results show that the extraction performance of key elements is superior,and the query of preferential tax policies is quick and intuitive,which can effectively alleviate the problem of massive tax preferential information overload.
作者
关海山
郑玉龙
魏笔凡
张泽民
岳浩
师斌
董博
GUAN Haishan;ZHENG Yulong;WEI Bifan;ZHANG Zemin;YUE Hao;SHI Bin;DONG Bo(School of Software Engineering,Xi’an Jiaotong University,Xi’an 710049,China;Shaanxi Key Laboratory of Satellite&Terrestrial Network Technology R&D,Xi’an 710049,China;School of Continuing Education,Xi’an Jiaotong University,Xi’an 710049,China;School of Computer Science and Technology,Xi’an Jiaotong University,Xi’an 710049,China)
出处
《大数据》
2022年第5期106-123,共18页
Big Data Research
基金
国家重点研发计划资助项目(No.2020AAA0108800)
国家自然科学基金资助项目(No.62137002,No.61937001,No.62176209,No.62176207,No.62106190,No.62050194)
国家自然科学基金创新研究群体资助项目(No.61721002)
教育部创新团队资助项目(No.IRT_17R86)
中国工程院咨询研究资助项目“基于MOOC中国的‘一带一路’人才培养的线上线下混合教学支撑信息化平台与服务体系”
中国博士后科学基金项目(No.2020M683493)
中国工程科技知识中心资助项目。
关键词
税收优惠政策
预训练语言模型
信息抽取
可视化
preferential tax policy
pre-trained language model
information extraction
visualization
