TY - GEN
T1 - PEPO
T2 - 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023
AU - Chiu, Yin Wei
AU - Huang, Hsiao Ching
AU - Lee, Cheng Ju
AU - Hsieh, Hsun Ping
N1 - Publisher Copyright:
© 2023 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2023/7/18
Y1 - 2023/7/18
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85168672589&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85168672589&partnerID=8YFLogxK
U2 - 10.1145/3539618.3591811
DO - 10.1145/3539618.3591811
M3 - Conference contribution
AN - SCOPUS:85168672589
T3 - SIGIR 2023 - Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 3150
EP - 3154
BT - SIGIR 2023 - Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
PB - Association for Computing Machinery, Inc
Y2 - 23 July 2023 through 27 July 2023
ER -