Google llc (20240161743). SELECTIVELY GENERATING EXPANDED RESPONSES THAT GUIDE CONTINUANCE OF A HUMAN-TO-COMPUTER DIALOG simplified abstract

SELECTIVELY GENERATING EXPANDED RESPONSES THAT GUIDE CONTINUANCE OF A HUMAN-TO-COMPUTER DIALOG

Organization Name

google llc

Inventor(s)

Michael Fink of Tel Aviv (IL)

Vladimir Vuskovic of Zolikerberg (CH)

Shimon Or Salant of Rechovot Center District (IL)

Deborah Cohen of Tel Aviv (IL)

Asaf Revach of Nordia Center District (IL)

David Kogan of Natick MA (US)

Andrew Callahan of Somerville MA (US)

Richard Borovoy of Boston MA (US)

Andrew Richardson of Cambridge MA (US)

Eran Ofek of Rdhovot (IL)

Idan Szpektor of Kfar Saba (IL)

Jonathan Berant of Tel Aviv (IL)

Yossi Matias of Tel Aviv (IL)

SELECTIVELY GENERATING EXPANDED RESPONSES THAT GUIDE CONTINUANCE OF A HUMAN-TO-COMPUTER DIALOG - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240161743 titled 'SELECTIVELY GENERATING EXPANDED RESPONSES THAT GUIDE CONTINUANCE OF A HUMAN-TO-COMPUTER DIALOG

Simplified Explanation

The patent application abstract describes a system for generating expanded responses in a human-to-computer dialog facilitated by a client device and an automated assistant. The expanded responses are based on user input and incorporate content related to entities not explicitly mentioned by the user.

• The system generates expanded responses in a human-to-computer dialog.
• The responses are based on user input provided via a client device.
• The automated assistant generates expanded responses incorporating content related to additional entities.
• The responses are rendered to the user via the client device.

Potential Applications

This technology could be applied in customer service chatbots, virtual assistants, and automated help desks to provide more comprehensive and relevant responses to user queries.

Problems Solved

This technology solves the problem of limited responses in automated dialog systems by expanding the scope of information provided to users based on their input.

Benefits

The benefits of this technology include improved user experience, increased efficiency in information retrieval, and more personalized interactions between users and automated assistants.

Potential Commercial Applications

One potential commercial application of this technology is in e-commerce customer service chatbots, where it can enhance the shopping experience by providing detailed information about products and services.

Possible Prior Art

One possible prior art for this technology could be natural language processing systems that generate responses based on user input, but may not specifically focus on expanding responses to include content related to additional entities.

How does the system determine which entities are related to the entity of interest in generating expanded responses?

The system uses semantic analysis and contextual understanding to determine the relationships between entities and identify relevant content to include in the responses.

What measures are in place to ensure the accuracy and relevance of the expanded responses generated by the automated assistant?

The system may incorporate machine learning algorithms and feedback mechanisms to continuously improve the quality of the responses and adapt to user preferences and needs.

Original Abstract Submitted

generating expanded responses that guide continuance of a human-to computer dialog that is facilitated by a client device and that is between at least one user and an automated assistant. the expanded responses are generated by the automated assistant in response to user interface input provided by the user via the client device, and are caused to be rendered to the user via the client device, as a response, by the automated assistant, to the user interface input of the user. an expanded response is generated based on at least one entity of interest determined based on the user interface input, and is generated to incorporate content related to one or more additional entities that are related to the entity of interest, but that are not explicitly referenced by the user interface input.