基于自然语言处理的请愿执行处理优化器

Yin-Wei Chiu, Hsiao-Ching Huang, Cheng-Ju Lee, Hsun-Ping Hsieh
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引用次数: 0

摘要

本文提出“信访执行流程优化器(PEPO)”,这是一个基于人工智能的信访处理系统,具有三个组成部分,(a)部门分类,(b)重要性评估和(c)响应生成,以改善台湾工务局(PWB) 1999年热线信访处理流程。我们的部门分类算法已经用NDCG进行了评估,获得了86.48%的高分,而重要评估函数的准确率达到了85%。此外,响应生成提高了政府与公民之间的沟通效率。PEPO系统已部署为台南市政府工务局的线上网路服务。有了《公民申诉条例》,工务局在处理公民申诉方面的成效和效率大大提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PEPO: Petition Executing Processing Optimizer Based on Natural Language Processing
In this paper, we propose "Petition Executing Process Optimizer (PEPO)," an AI-based petition processing system that features three components, (a) Department Classification, (b) Importance Assessment, and (c) Response Generation for improving the Public Work Bureau (PWB) 1999 Hotline petitions handling process in Taiwan. Our Department Classification algorithm has been evaluated with NDCG, achieving an impressive score of 86.48%, while the Important Assessment function has an accuracy rate of 85%. Besides, Response Generation enhances communication efficiency between the government and citizens. The PEPO system has been deployed as an online web service for the Public Works Bureau of the Tainan City Government. With PEPO, the PWB benefits greatly from the effectiveness and efficiency of handling citizens' petitions.
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