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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
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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
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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.
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