Using Customer Service Dialogues for Satisfaction Analysis with Context-Assisted Multiple Instance Learning

IJCNLP 2019 Kaisong SongLidong BingWei GaoJun LinLujun ZhaoJiancheng WangChanglong SunXiaozhong LiuQiong Zhang

Customers ask questions and customer service staffs answer their questions, which is the basic service model via multi-turn customer service (CS) dialogues on E-commerce platforms. Existing studies fail to provide comprehensive service satisfaction analysis, namely satisfaction polarity classification (e.g., well satisfied, met and unsatisfied) and sentimental utterance identification (e.g., positive, neutral and negative)... (read more)

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