Papers with CAMIL) model

1 papers
Using Customer Service Dialogues for Satisfaction Analysis with Context-Assisted Multiple Instance Learning (D19-1)

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Challenge: Existing studies fail to provide comprehensive service satisfaction analysis . Existing models fail to include satisfaction polarity classification and sentimental utterance identification .
Approach: They propose a model that predicts customer sentiments and aggregates them into service satisfaction polarity.
Outcome: The proposed model predicts customer sentiments and aggregates them into service satisfaction polarity and reasoning clues.

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