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SYSTEM AND METHOD OF SENTIMENT MODELING AND APPLICATION TO DETERMINE OPTIMIZED AGENT ACTION

机译:情绪建模的系统和方法和应用方法,以确定优化的代理动作

摘要

The present invention is a system and method of continuous sentiment tracking and the determination of optimized agent actions through the training of sentiment models and applying the sentiment models to new incoming interactions. The system receives conversations comprising incoming interactions and agent actions and determines customer sentiment on a micro-interaction level for each incoming interaction. Based on interaction types, the system corelates the determined sentiment with the agent action received prior to the sentiment determination to create and train sentiment models. Sentiment models include agent action recommendations for a desired sentiment outcome. Once trained, the sentiment models can be applied to new incoming interactions to provide CSRs with actions that will yield a desired sentiment outcome.
机译:本发明是一种通过对情绪模型的训练和将情绪模型应用于新的传入交互来连续情绪跟踪的系统和方法和确定优化的代理动作。该系统接收包括传入交互和代理操作的对话,并确定每个输入交互的微交互水平的客户情绪。基于交互类型,系统将所确定的情绪与在情绪决定之前收到的代理行动,以创建和培训培训情绪模型。情绪模型包括代理行动建议,了解所需的情绪结果。培训后,情绪模型可以应用于新的传入交互,以提供CSR的动作,以产生所需的情绪结果。

著录项

  • 公开/公告号WO2021076498A1

    专利类型

  • 公开/公告日2021-04-22

    原文格式PDF

  • 申请/专利权人 VERINT AMERICAS INC.;

    申请/专利号WO2020US55386

  • 发明设计人 JOHNSTON MICHAEL;

    申请日2020-10-13

  • 分类号G06F40/30;G06F40/216;G06Q30;

  • 国家 US

  • 入库时间 2022-08-24 18:22:08

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