首页> 外国专利> METHODOLOGY TO AUTOMATICALLY INCORPORATE FEEDBACK TO ENABLE SELF LEARNING IN NEURAL LEARNING ARTIFACTORIES

METHODOLOGY TO AUTOMATICALLY INCORPORATE FEEDBACK TO ENABLE SELF LEARNING IN NEURAL LEARNING ARTIFACTORIES

机译:自动整合反馈以在神经学习人工工具中实现自我学习的方法

摘要

Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons. Any ML algorithm can use, or operate in conjunction with, a neural knowledge artifactory comprising the knowledge neurons to enhance or improve baseline accuracy, for example during a cold start period, for augmented decision making and/or for labeling data points or establishing ground truth to perform supervised learning.
机译:公开了用于生成,增强,应用和更新知识神经元以向各种客户端应用提供决策信息的方法,技术和机制。知识领域的领域关键字是根据选定领域数据源的领域数据以及领域关键字的关键字值生成的,用于生成知识工件,以包含在知识神经元中。可以通过在各种数据源中找到的领域知识数据集来增强这些知识神经元,这些领域知识数据集可用于生成对从客户端应用程序接收的神经查询的神经响应。神经反馈可用于更新和/或生成知识神经元。任何ML算法都可以使用或与包含知识神经元的神经知识文物一起使用,或与之结合操作,以增强或改善基线准确度,例如在冷启动期间,用于增强决策和/或标记数据点或建立基本事实进行监督学习。

著录项

  • 公开/公告号US2020012931A1

    专利类型

  • 公开/公告日2020-01-09

    原文格式PDF

  • 申请/专利权人 GLOBAL ELMEAST INC.;

    申请/专利号US201816029106

  • 发明设计人 MANOJ PRASANNA KUMAR;

    申请日2018-07-06

  • 分类号G06N3/08;G06N3/04;

  • 国家 US

  • 入库时间 2022-08-21 11:18:45

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