US-20260127352-A1 - VIRTUAL SPACE GENERATOR

US20260127352A1US 20260127352 A1US20260127352 A1US 20260127352A1US-20260127352-A1

Abstract

Techniques for transforming the structural formatting of content are described herein. A communication platform may receive a request from a user profile to transform the structural formatting of content included in an initial virtual space. The communication platform may receive user input data that represents one or more instructions regarding a type of new virtual space to generate. The communication platform may input the instruction(s) and/or content of the initial virtual space into one or more machine learned models that are trained to generate specific types of virtual spaces that include different types of formatting structures. The communication platform may receive the new virtual space from the machine learned model(s) and cause the new virtual space to be displayed via a user interface of a user device.

Inventors

Blaine Scott Billingsley
Christina Mudarth
Rafael Amsili
Melissa Aubrie Chan
Kevin Shih

Assignees

SALESFORCE, INC.

Dates

Publication Date: 20260507
Application Date: 20241104

Claims (20)

1 . A system comprising: one or more processors; and one or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause the one or more processors to perform operations comprising: receiving, from a user profile associated with a group-based communication platform and from within a first virtual space associated with the group-based communication platform, a request to modify a first structural formatting of content within the first virtual space; causing, in response to receiving the request, a custom prompt to be displayed via a user interface of a user device; receiving, from the user profile, user input data representative of a selection of one or more instructions associated with the custom prompt; inputting the one or more instructions and the content into a first machine learned model trained to modify the content by performing one or more operations to the content; receiving, from the first machine learned model, first output data; inputting the first output data into a second machine learned model trained to transform the content from the first structural formatting to a second structural formatting; receiving, from the second machine learned model, second output data representing a second virtual space that includes the second structural formatting that is different than the first structural formatting of the first virtual space; and causing, in response to receiving the second output data, the second output data to be displayed via the user interface of the user device associated with the user profile.
2 . The system of claim 1 , wherein the custom prompt is determined based at least in part on: identifying a header or a column of data within the first virtual space, wherein the custom prompt includes the header or the column.
3 . The system of claim 1 , the operations further comprising: causing the second virtual space to be associated with the first virtual space; and determining, in response to associating the second virtual space with the first virtual space, that the second virtual space is accessible to one or more members of the first virtual space.
4 . The system of claim 1 , wherein the one or more instructions include an instruction to transform the content in the first virtual space according to the user input data at a predetermined frequency.
5 . The system of claim 1 , wherein receiving the first output data is further based at least in part on: determining context data associated with one or more previous interactions of the user profile with the group-based communication platform; and inputting the context data into the first machine learned model, wherein receiving the first output data is based at least in part on inputting the context data into the first machine learned model.
6 . The system of claim 1 , wherein the first virtual space is a first type of virtual space and the second virtual space is a second type of virtual space that is different than the first type.
7 . One or more non-transitory computer-readable media storing instructions executable by one or more processors, wherein the instructions, when executed, cause the one or more processors to perform operations comprising: receiving, from a user profile associated with a group-based communication platform and from within a first virtual space associated with the group-based communication platform, a request to modify a first structural formatting of content within the first virtual space; receiving, from the user profile, user input data representative of one or more instructions; inputting the one or more instructions and the content into a first machine learned model trained to modify the content by performing one or more operations to the content; receiving, from the first machine learned model, first output data; inputting the first output data into a second machine learned model trained to transform the content from the first structural formatting to a second structural formatting; receiving, from the second machine learned model, second output data representing a second virtual space that includes the second structural formatting that is different than the first structural formatting of the first virtual space; and causing, in response to receiving the second output data, the second output data to be displayed via a user interface of a user device associated with the user profile.
8 . The one or more non-transitory computer-readable media of claim 7 , the operations further comprising: causing, in response to receiving the request, a custom prompt to be displayed via a user interface of a user device, wherein the custom prompt includes the one or more instructions.
9 . The one or more non-transitory computer-readable media of claim 8 , wherein the custom prompt is determined based at least in part on: identifying a header or a column of data within the first virtual space, wherein the custom prompt includes the header or the column.
10 . The one or more non-transitory computer-readable media of claim 7 , the operations further comprising: causing the second virtual space to be associated with the first virtual space; and determining, in response to associating the second virtual space with the first virtual space, that the second virtual space is accessible to one or more members of the first virtual space.
11 . The one or more non-transitory computer-readable media of claim 7 , wherein the one or more instructions include an instruction to transform the content in the first virtual space according to the user input data at a predetermined frequency.
12 . The one or more non-transitory computer-readable media of claim 7 , wherein receiving the first output data is further based at least in part on: determining context data associated with one or more previous interactions of the user profile with the group-based communication platform; and inputting the context data into the first machine learned model, wherein receiving the first output data is based at least in part on inputting the context data into the first machine learned model.
13 . The one or more non-transitory computer-readable media of claim 7 , wherein the first virtual space is a first type of virtual space and the second virtual space is a second type of virtual space that is different than the first type.
14 . A method comprising: receiving, from a user profile associated with a group-based communication platform and from within a first virtual space associated with the group-based communication platform, a request to modify a first structural formatting of content within the first virtual space; receiving, from the user profile, user input data representative of one or more instructions; inputting the one or more instructions and the content into a first machine learned model trained to modify the content by performing one or more operations to the content; receiving, from the first machine learned model, first output data; inputting the first output data into a second machine learned model trained to transform the content from the first structural formatting to a second structural formatting; receiving, from the second machine learned model, second output data representing a second virtual space that includes the second structural formatting that is different than the first structural formatting of the first virtual space; and causing, in response to receiving the second output data, the second output data to be displayed via a user interface of a user device associated with the user profile.
15 . The method of claim 14 , the method further comprising: causing, in response to receiving the request, a custom prompt to be displayed via a user interface of a user device, wherein the custom prompt includes the one or more instructions.
16 . The method of claim 15 , wherein the custom prompt is determined based at least in part on: identifying a header or a column of data within the first virtual space, wherein the custom prompt includes the header or the column.
17 . The method of claim 14 , the method further comprising: causing the second virtual space to be associated with the first virtual space; and determining, in response to associating the second virtual space with the first virtual space, that the second virtual space is accessible to one or more members of the first virtual space.
18 . The method of claim 14 , wherein the one or more instructions include an instruction to transform the content in the first virtual space according to the user input data at a predetermined frequency.
19 . The method of claim 14 , wherein receiving the first output data is further based at least in part on: determining context data associated with one or more previous interactions of the user profile with the group-based communication platform; and inputting the context data into the first machine learned model, wherein receiving the first output data is based at least in part on inputting the context data into the first machine learned model.
20 . The method of claim 14 , wherein the first virtual space is a first type of virtual space and the second virtual space is a second type of virtual space that is different than the first type.

Description

TECHNICAL FIELD Communication platforms are becoming increasingly more popular for organizations to facilitate work related communications. Such communication platforms may include a variety of different types of virtual spaces which may facilitate the communication and/or interaction amongst users. However, in some cases, techniques for managing and/or maintaining the virtual spaces can result in users spending excessive amounts of time manually performing operations which may disrupt the user experience. BRIEF DESCRIPTION OF THE DRAWINGS The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different figures indicates similar or identical components or features. The figures are not drawn to scale. FIG. 1 illustrates an example system for performing techniques described herein. FIG. 2A illustrates a user interface for a group-based communication system for certain examples. FIG. 2B illustrates a user interface for multimedia collaboration sessions within the group-based communication system for certain examples. FIG. 2C illustrates a user interface for inter-organization collaboration within the group-based communication system for certain examples. FIG. 2D illustrates a user interface for collaborative documents within the group-based communication system for certain examples. FIG. 3A depicts a user interface for workflows within a group-based communication system. FIG. 3B depicts a block diagram for carrying out certain examples, as discussed herein. FIG. 4 is a block diagram illustrating the interactions of components of a format transformation component configured to modify the formatting of content in a virtual space. FIG. 5 is an example user interface illustrating a custom prompt. FIG. 6 is an example user interface illustrating the transformation of the structure of data within different virtual spaces. FIG. 7 is a flow diagram illustrating an example process for requesting a change in content structure, receiving instruction(s), generating a new virtual space based on the instruction(s), and causing the new virtual space to be displayed to a user device. DETAILED DESCRIPTION As described above, conventional techniques for managing and/or maintaining data within a virtual space may result in an inefficient and/or suboptimal user experience. Techniques for transforming the structural formatting of content is described herein. In some examples, a communication platform may receive a request from a user profile to transform the structural formatting of content contained an initial virtual space (e.g., channel, direct messaging instance, multiparty direct messaging instance, board, canvas, etc.). Based on the request, the communication platform may display a custom prompt that allows the user profile to indicate the type of virtual space to transform the content into and/or which content from the initial virtual space to include in the transformation. The communication platform may receive user input data that represents a selection of one or more instructions from the custom prompt. The communication platform may input the instruction(s) and/or the content of the initial virtual space into a first machine learned model that is trained to generate input data for a second machine learned model. Based on receiving the input data from the first machine learned model, the communication platform may input the input data into the second machine learned model which may be trained to generate specific types of virtual spaces that include different types of formatting structures. In some examples, the communication platform may receive the new virtual space from the second machine learned model and cause the new virtual space to be displayed via a user interface of a user device. As discussed throughout this disclosure, the techniques may improve the user experience by enabling users to convert or otherwise transform the formatting of content within a virtual space to be optimal and/or efficient for comprehension. When managing and/or maintaining data within a communication platform, it may be beneficial to modify the formatting of the data such as to optimize the understanding and/or accessibility of the data. For example, a user profile can use a virtual space such as a canvas that is associated with a communication channel. The user profile may use the canvas to maintain data associated with the channel and/or the user profiles associated therewith. However, in some circumstances, the user profile (or any other user profile of the communication channel) may determine that the data contained in the canvas would be better contained, represented, and/or understood in a list (or spreadsheet) virtual space. In such cases, the user profile may spend excessive amounts of time manually transferring the data from the canvas to