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Predicting Business-Agnostic Contact Center Expected Wait Times With Deep Neural Networks

机译:使用深度神经网络预测与业务无关的联络中心的预期等待时间

摘要

A method for predicting an estimated wait time includes receiving a pending support request from a user. The pending support request is associated with a plurality of high-level features that include a number of active support agents, a number of available support agents, and a queue depth. The method also includes predicting an estimated wait time for the user of the pending support request using a wait time predictor model configured to receive the plurality of high-level features as feature inputs. The wait time predictor model is trained on a corpus of training support requests that include corresponding high-level features and a corresponding actual wait time. The method also includes providing the estimated wait time to the user that indicates an estimated duration of time until the pending support request is answered.
机译:一种预测估计等待时间的方法,包括从用户接收待处理的支持请求。未决支持请求与多个高级功能相关联,这些高级功能包括多个活动支持代理,多个可用支持代理以及队列深度。该方法还包括使用配置为接收多个高级特征作为特征输入的等待时间预测器模型,为待处理的支持请求的用户预测估计的等待时间。在一组训练支持请求上训练了等待时间预测变量模型,该训练支持请求包括相应的高级功能和相应的实际等待时间。该方法还包括向用户提供估计的等待时间,该估计的等待时间指示直到应答未决的支持请求为止的估计的持续时间。

著录项

  • 公开/公告号US2020334615A1

    专利类型

  • 公开/公告日2020-10-22

    原文格式PDF

  • 申请/专利权人 GOOGLE LLC;

    申请/专利号US201916390409

  • 发明设计人 ALEX BENJAMIN;YASH SHAH;

    申请日2019-04-22

  • 分类号G06Q10/06;G06Q30;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-21 11:24:35

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