An AI-based Approach for Mystery Shopping Audit in Customer Service
學年 112
學期 2
發表日期 2024-05-22
作品名稱 An AI-based Approach for Mystery Shopping Audit in Customer Service
作品名稱（其他語言）
著者 Christopher Chuang; Qiaoyun Zhang; Yi-Ti Lin; Chia-Ling Ho; Chih-Yung Chang
作品所屬單位
出版者
會議名稱 I-DO 2024
會議地點 Taipei; Taiwan
摘要 In the era of intense business competition, the emergence of mystery shoppers provides companies with objective insights, enabling them to innovate and enhance their offerings to meet evolving customer needs and maintain a competitive edge. This paper introduces AMSA (AI-based approach for Mystery Shopping Audit), a service behavior identification mechanism for analyzing mystery shopping audit videos. AMSA identifies behaviors like five-finger guidance, hand offering, and maintaining good posture through two phases: coarse-grain and fine-grain identification. In the coarse-grain phase, an automated filtering and classification algorithm is proposed, utilizing YOLO for target detection. Subsequently, fine-grain identification employs 3DCNN for action classification, trained on enhanced videos of target actions. The Simulation results show that the proposed AMSA significantly improves accuracy of identification.
關鍵字
語言 zh_TW
收錄於
會議性質 國內
校內研討會地點 無
研討會時間 20240522~20240524
通訊作者
國別 TWN
公開徵稿
出版型式
出處
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/126361 )

SDGS 尊嚴就業與經濟發展,產業創新與基礎設施