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• W4240216186 abstract "As conversational CRM systems communicate with human customers and not other computer systems, they need to tackle human emotions in a way to optimize the outcome of a chatbot session. A chatbot needs to understand the emotions of its peers and produce utterances which not only match their emotional states but also attempt to improve it towards solving a problem. We construct a model and a training dataset of emotions and personality from various sources to properly react to the customer in the emotional space and to navigate him through it. We evaluated an overall contribution of a chatbot enabled with affective computing and observed up to 18% boost in the relevance of responses, as perceived by customers." @default.
• W4240216186 created "2022-05-12" @default.
• W4240216186 creator A5071035935 @default.
• W4240216186 date "2020-12-24" @default.
• W4240216186 modified "2023-10-16" @default.
• W4240216186 title "Adjusting Chatbot Conversation to User Personality and Mood" @default.
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• W4240216186 doi "https://doi.org/10.1007/978-3-030-61641-0_3" @default.
• W4240216186 hasPublicationYear "2020" @default.
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