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基于TF-IDF和jieba分词的交通运输综合执法语音文件和文本文件关联匹配技术

TF-IDF-Based Transportation Integrated Law Enforcement Voice File and Text File Association Matching Technology
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摘要 在交通运输综合行政执法听证环节中,传统听证环节均是线下举行的,听证记录员需要对整个听证环节的笔录进行详细记录。由于会后需要与整个案件的证据材料进行归档整理,对于执法人员的工作强度要求很高。因此,针对交通运输综合执法办案流程中的听证业务环节提供一定的技术支撑,利用TF-IDF算法对听证内容进行关键词提取,和jieba分词进行优化开发语音文件和文本文件关联匹配技术,实现听证语音文本与案件关键要素信息的精确关联匹配,构建完整证据链确保行政处罚有据可依,整体提升交通运输综合行政执法针对听证案件的处罚判决的充分与准确,助力政府治理系统和治理能力现代化建设。 In the comprehensive administrative law enforcement hearing process of transportation, the traditional hearing process is held offline, and the hearing recorder needs to keep detailed records of the entire hearing process. Due to the need to archive and organize the evidence materials of the entire case after the meeting, there is a high demand for the workload of law enforcement personnel. To provide certain technical support for the hearing business process in the comprehensive law enforcement process of transportation, TF-IDF algorithm is used to extract key words from the hearing content, and jieba segmentation is used to optimize the development of voice evidence files and text file association matching technology, Realize accurate correlation and matching between hearing voice text and key element information of the case, construct a complete evidence chain to ensure that administrative penalties are based on evidence, comprehensively improve the adequacy and accuracy of punishment judgments for hearing cases in transportation comprehensive administrative law enforcement, and assist in the modernization of government governance system and governance capacity.
出处 《交通技术》 2023年第5期377-384,共8页 Open Journal of Transportation Technologies
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