Titlebook: Artificial Intelligence for Customer Relationship Management; Solving Customer Pro Boris Galitsky Book 2021 The Editor(s) (if applicable) a

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Demographic and Biological Applications, concept learning technique for common scenarios of interaction between conflicting human agents. Customer complaints are classified as valid (requiring some kind of compensation) or invalid (requiring reassuring and calming down) the customer. Scenarios are represented by directed graphs with label

周兴旺

Demographic and Biological Applications,d produces the consecutive mental states as plausible to a real-world scenario as possible. We simulate a multiagent decision-making environment taking into account intentions, knowledge and beliefs of itself and others. The simulation results are evaluated with respect to precision, completeness an

草率男

Holm Altenbach,Vladimir A. Kolupaevdepartment. We explore a technology that can detect this performance and a root cause for it, in terms of We explore the phenomenon of Distributed Incompetence (DI), which is an opposite to Distributed Knowledge and occurs in various organizations such as customer support. In a DI organization, a te

Contort

Boris GalitskyIntroduces a number of dialogue management algorithms to drive a user through multiple ways of solving his problem.Explains how to detect misinformation, fake content and deception relying on discours

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Human–Computer Interaction Serieshttp://image.papertrans.cn/b/image/162361.jpg

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More on Exponential Representation,attempt to resolve it, along with receiving a recommendation for a product with features addressing this problem. The performance of RJC is evaluated in a number of human–human and human-chatbot dialogues and demonstrates that RJC is an efficient and less intrusive way to provide high relevance and persuasive recommendations.

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