首页>
外国专利>
GENERATING A SELECTABLE SUGGESTION USING A PROVISIONAL MACHINE LEARNING MODEL WHEN USE OF A DEFAULT SUGGESTION MODEL IS INCONSEQUENTIAL
GENERATING A SELECTABLE SUGGESTION USING A PROVISIONAL MACHINE LEARNING MODEL WHEN USE OF A DEFAULT SUGGESTION MODEL IS INCONSEQUENTIAL
展开▼
机译：使用默认建议模型时使用临时机器学习模型生成可选择的建议是无关紧要的
展开▼
页面导航
摘要
著录项
相似文献
摘要
Implementations set forth herein relate to selectively relying on additional suggestion model(s) when generating selectable suggestions, while also maintaining access to a default suggestion model. The selectable suggestions can be generated using one or more additional multi-domain machine learning (ML) models, which can be optionally available to the client application, regardless of whether a default suggestion model remains useful for generating suitable suggestions. In some implementations, as the client application employs various additional multi-domain ML models, a particular model can be identified as improving suggestions for the client application, at least based on user feedback and/or other data. The particular model can then be selected to replace and/or supplement the default suggestion model, in order to provide more accurate suggestions that, when selected, initialize actions that can preserve time and computational resources.
展开▼
