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Directed acyclic graph based framework for training models

机译:基于训练模型的基于框架的针对性曲线图

摘要

Techniques for chatbots, and more particularly, to techniques for using a directed acyclic graph (DAG) based framework to build and train models. In one particular aspect, a computer implemented method is provided that includes generating, by a DAG based framework, a first model and a second model, executing the first model for a chatbot in run-time and second model for the chatbot in design-time, collecting attributes for intent classification associated with a set of utterances with the chatbot running the first model and the second model, evaluating, using one or more metrics, performance of the first model and the second model based on an analysis of the attributes for the intent classification, determining whether the performance of the second model is improved as compared to the performance of the first model, and executing the first model or the second model for the chatbot in run-time based on the performance determination.
机译:聊天禁令的技术,更具体地,是使用基于有向非循环图(DAG)的框架来构建和培训模型的技术。 在一个特定方面中,提供了一种计算机实现的方法,包括由基于DAG的框架,第一模型和第二模型生成,用于在设计时为Chatbot中的运行时间和第二模型中执行第一个模型以进行Chatbot的第一个模型 ,收集与一组话语相关的意图分类,其中包含运行第一模型的聊天和第二种模型,使用一个或多个度量,第一个模型的性能和第二模型的性能,基于对属性的分析 目的分类,确定与第一个模型的性能相比改进了第二模型的性能,以及在基于性能确定的运行时执行第一模型或第二模型。

著录项

  • 公开/公告号US11206229B2

    专利类型

  • 公开/公告日2021-12-21

    原文格式PDF

  • 申请/专利权人 ORACLE INTERNATIONAL CORPORATION;

    申请/专利号US202016823611

  • 发明设计人 GAUTAM SINGARAJU;CRYSTAL PAN;

    申请日2020-03-19

  • 分类号H04L12/58;G06F16/901;G06K9/62;

  • 国家 US

  • 入库时间 2022-08-24 22:55:30

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