コンテキストにわたる意味的に関連するコンピューティングタスクの自動化

Abstract

The disclosed embodiments relate to automating semantically similar computing tasks across multiple contexts. In various implementations, an initial natural language input and a first plurality of actions to be performed using a first computer application can be used to generate a first task embedding and a first action embedding in an action embedding space. An association between the first task embedding and the first action embedding can be stored. Later, a subsequent natural language input can be used to generate a second task embedding, which is then matched with the first task embedding. Based on the stored association, the first action embedding can be identified and processed using a selected domain model to select an action to be performed using the second computer application. The selected domain model can be trained to transform between the action space and the action embedding space of the second computer application.

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