PEPO: Petition Executing Processing Optimizer Based on Natural Language Processing

被引：1

作者：

Chiu, Yin-Wei ^{[1
]}

Huang, Hsiao-Ching ^{[1
]}

Lee, Cheng-Ju ^{[1
]}

Hsieh, Hsun-Ping ^{[1
]}

机构：

[1] Natl Cheng Kung Univ, Dept Elect Engn, Tainan, Taiwan

来源：

PROCEEDINGS OF THE 46TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2023 | 2023年

关键词：

Natural language processing; Complaint analysis; Text classification; Text extraction;

D O I：

10.1145/3539618.3591811

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：3150 / 3154

页数：5

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