Virtual assistant for generating personalized responses within a communication session

Abstract

Intelligent agents (IA) for automatically generating responses to content within a communication session (CS) are disclosed. An IA is trained to target the responses to a user and the user's context within the CS. An IA receives CS content that includes natural language expressions encoding users' conversations and determines content features based on natural language models. The content featuresindicate intended semantics of the expressions. The IA identifies likely-relevant content to the targeted user, to generate a response for. Identifying such content includes determining a relevance ofthe content based on content features, a context of the CS, a user-interest model, and a content-relevance model. Identifying the likely-relevant content to respond to is based on the determined relevance of the content and relevance thresholds. Various responses to the identified portions of the content are automatically generated and provided based on a natural language response-generation model targeted to the user.

Description

Background technique [0001] Increasingly, people find themselves multitasking among multiple jobs distributed across multiple computing interfaces, applications, platforms, displays, and devices. For example, due to the growing popularity of networked computing, users can now simultaneously participate in one or more communication sessions, such as chat or instant messaging (IM) sessions, while simultaneously shopping online, generating work-related documents, scheduling vehicle maintenance, or other multiple tasks. [0002] Active participation in a communication session often requires reading (or otherwise consuming), processing, and responding to conversations within the communication session. Thus, even though a computing device enables a user to simultaneously engage in separate and distinct tasks, the user may still experience difficulties in the real-time performance of various functions associated with each task. For example, it is active for users to monitor, track,...

AI Technical Summary

Problems solved by technology

As a result, users attempting to multitask may appear unresponsive and / or disengaged to other users.

Additionally, users may lose the opportunity to contribute their unique perspective to the conversation

Put more succinctly, the utility and user experience of a real-time communication session can be degraded when a user attempts to divide their attention across multiple tasks

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