淡江大學機構典藏:Item 987654321/126361
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    題名: An AI-based Approach for Mystery Shopping Audit in Customer Service
    作者: Chuang, Christopher;Zhang, Qiaoyun;Lin, Yi-Ti;Ho, Chia-Ling;Chang, Chih-Yung
    日期: 2024-05-22
    上傳時間: 2024-10-07 12:06:07 (UTC+8)
    出版者: Association for Computing Machinery,New York,NY,United States
    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.
    DOI: 10.1145/3658549.3658555
    顯示於類別:[資訊工程學系暨研究所] 會議論文

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