# US 12,120,075 B2 · Transitioning between private and non-private state

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 12,120,075 B2
- Document ID: US12120075B2
- Status: Granted
- Kind: B2
- Application number: 18/204,119
- Filed: 2023-05-31
- Published: 2023-09-28
- Granted: 2024-10-15
- Earliest claimed: 2017-02-17
- Assignees: Google Inc.
- Applicants: Google LLC
- Inventors: Sandro Feuz; Sebastian Millius
- Web page: https://patentgrep.com/patent/US12120075B2

## CPC

- H04L 51/063: Content adaptation, e.g. replacement of unsuitable content
- G06Q 10/10: Office automation; Time management
- G06Q 10/107: Computer-aided management of electronic mailing [e-mailing]
- H04L 51/216: Handling conversation history, e.g. grouping of messages in sessions or threads
- H04L 51/04: Real-time or near real-time messaging, e.g. instant messaging [IM]
- H04L 51/52: for supporting social networking services
- H04L 67/535: {Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34)}
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

This specification is generally directed to techniques for automatically transitioning applications—especially those that enable exchange of messages between users—into and/or out of a private state based on a variety of signals associated with the messages and/or the participants themselves. In various implementations, an ongoing message exchange thread between two or more participants operating two or more respective message exchange clients may be examined. Based at least in part on the examining, a likelihood may be determined that message(s) directed by one of the participants to another of the participants as part of the ongoing message exchange thread would be deemed private by at least a given participant of the two or more participants. A determination may be made of whether the determined likelihood satisfies one or more thresholds, and in response, one or more of the message exchange clients may be transitioned into a private state.

## Claims

### Claim 1

A method implemented using one or more processors and comprising:
examining an ongoing message exchange thread between two or more participants operating two or more respective message exchange clients;
applying a plurality of inputs across a machine learning model to predict a likelihood that one or more messages directed by one of the two or more participants to another of the two or more participants as part of the ongoing message exchange thread would be deemed private by at least a given participant of the two or more participants, wherein the machine learning model is trained to provide, based on the plurality of inputs, output that includes the predicted likelihood, and wherein the plurality of inputs include at least one input associated with the given participant and another input corresponding to the one or more messages directed by one or more of the two or more participants to the another of the two or more participants;
determining that the likelihood satisfies a first threshold;
determining that the likelihood satisfies a second threshold;
automatically transitioning a first message exchange client one or more of the two or more message exchange clients into a private state in response to determining that the likelihood satisfies the first threshold; and
transmitting, to a second message exchange client of the two or more message exchange clients, a command that causes the second message exchange client to transition to the private state, wherein the transmitting is performed in response to determining that the determined likelihood satisfies the first or second thresholds.

### Claim 2 (depends on 1)

The method of claim 1, wherein the machine learning model comprises a neural network.

### Claim 3 (depends on 1)

The method of claim 1, wherein the machine learning model is trained using labeled training examples associated with historical instances of message exchange threads in which message exchange thread participants manually transitioned message exchange clients into private states.

### Claim 4 (depends on 3)

The method of claim 3, wherein features of the labeled training examples include n-grams contained in the historical instances of message exchange threads.

### Claim 5 (depends on 3)

The method of claim 3, wherein features of the labeled training examples include phrases contained in the historical instances of message exchange threads.

### Claim 6 (depends on 3)

The method of claim 3, wherein features of the labeled training examples include contextual cues associated with participants of the historical instances of message exchange threads.

### Claim 7 (depends on 1)

The method of claim 1, further comprising:
causing a prompt to be rendered at one or more of the message exchange clients in response to determining that the likelihood satisfies the second threshold, wherein the prompt solicits permission to transition one or more of the two or more message exchange clients into a private state.

### Claim 8

A system comprising one or more processors and memory storing instructions that, in response to execution by the one or more processors, cause the one or more processors to:
examine an ongoing message exchange thread between two or more participants operating two or more respective message exchange clients;
apply a plurality of inputs across a machine learning model to predict a likelihood that one or more messages directed by one of the two or more participants to another of the two or more participants as part of the ongoing message exchange thread would be deemed private by at least a given participant of the two or more participants, wherein the machine learning model is trained to provide, based on the plurality of inputs, output that includes the predicted likelihood, and wherein the plurality of inputs include at least one input associated with the given participant and another input corresponding to the one or more messages directed by one or more of the two or more participants to the another of the two or more participants;
determine that the likelihood satisfies a first threshold;
determining that the likelihood satisfies a second threshold;
automatically transition a first message exchange client one or more of the two or more message exchange clients into a private state in to determining that the likelihood satisfies the first threshold; and
transmit, to a second message exchange client of the two or more message exchange clients, a command that causes the second message exchange client to transition to the private state, wherein the transmitting is performed in response to determining that the determined likelihood satisfies the first or second thresholds.

### Claim 9 (depends on 8)

The system of claim 8 wherein the machine learning model comprises a neural network.

### Claim 10 (depends on 8)

The system of claim 8 wherein the machine learning model is trained using labeled training examples associated with historical instances of message exchange threads in which message exchange thread participants manually transitioned message exchange clients into private states.

### Claim 11 (depends on 10)

The system of claim 10, wherein features of the labeled training examples include n-grams contained in the historical instances of message exchange threads.

### Claim 12 (depends on 10)

The system of claim 10, wherein features of the labeled training examples include phrases contained in the historical instances of message exchange threads.

### Claim 13 (depends on 10)

The system of claim 10, wherein features of the labeled training examples include contextual cues associated with participants of the historical instances of message exchange threads.

### Claim 14 (depends on 8)

The system of claim 8 further comprising instructions to: cause a prompt to be rendered at one or more of the message exchange clients in response to determining that the likelihood satisfies the second threshold, wherein the prompt solicits permission to transition one or more of the two or more message exchange clients into a private state.

### Claim 15

At least one non-transitory computer-readable medium comprising instructions that, in response to execution by one or more processors, cause the one or more processors to:
examine an ongoing message exchange thread between two or more participants operating two or more respective message exchange clients;
apply a plurality of inputs across a machine learning model to predict a likelihood that one or more messages directed by one of the two or more participants to another of the two or more participants as part of the ongoing message exchange thread would be deemed private by at least a given participant of the two or more participants, wherein the machine learning model is trained to provide, based on the plurality of inputs, output that includes the predicted likelihood, and wherein the plurality of inputs include at least one contextual cue generated by a computing device operated by the given participant and another input comprising content of the message exchange thread;
determine that the likelihood satisfies a first threshold;
determining that the likelihood satisfies a second threshold;
automatically transition a first message exchange client one or more of the two or more message exchange clients into a private state in to determining that the likelihood satisfies the first threshold; and
transmit, to a second message exchange client of the two or more message exchange clients, a command that causes the second message exchange client to transition to the private state, wherein the transmitting is performed in response to determining that the determined likelihood satisfies the first or second thresholds.

### Claim 16 (depends on 15)

The at least one non-transitory computer-readable medium of claim 15, wherein the machine learning model comprises a neural network.

### Claim 17 (depends on 15)

The at least one non-transitory computer-readable medium of claim 15, wherein the machine learning model is trained using labeled training examples associated with historical instances of message exchange threads in which message exchange thread participants manually transitioned message exchange clients into private states.

### Claim 18 (depends on 17)

The at least one non-transitory computer-readable medium of claim 17, wherein features of the labeled training examples include n-grams contained in the historical instances of message exchange threads.

### Claim 19 (depends on 17)

The at least one non-transitory computer-readable medium of claim 17, wherein features of the labeled training examples include phrases contained in the historical instances of message exchange threads or contextual cues associated with participants of the historical instances of message exchange threads.

### Claim 20 (depends on 15)

The at least one non-transitory computer-readable medium of claim 15, further comprising instructions to:
cause a prompt to be rendered at one or more of the message exchange clients in response to determining that the likelihood satisfies the second threshold, wherein the prompt solicits permission to transition one or more of the two or more message exchange clients into a private state.