Collaborative communication triage assistance

US11803703B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11803703-B2
Application numberUS-202117332169-A
CountryUS
Kind codeB2
Filing dateMay 27, 2021
Priority dateMay 27, 2021
Publication dateOct 31, 2023
Grant dateOct 31, 2023

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  1. Title

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  2. Abstract

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

Systems, storage media and methods for providing information for user prioritization of tasks associated with collaboratively developed content are described. Some examples may include: receiving a conversation thread associated with collaboratively developed content, the conversation thread including a plurality of comments authored by multiple different authors, generating a predicted measure of completion for the received conversation thread, the predicted measure of completion being at least one of a predicted number of remaining actions until the received conversation thread is resolved or a predicted number of total actions for the conversation thread to be resolved and providing, for display at a user interface, the predicted measure of completion for the received conversation thread, the predicted measure of completion being associated with the conversation thread at the user interface.

First claim

Opening claim text (preview).

What is claimed is: 1. A system, comprising: one or more hardware processors configured by machine-readable instructions to: receive a conversation thread associated with collaboratively developed content, the conversation thread including a plurality of comments authored by multiple different authors; generate a predicted measure of completion for the received conversation thread, the predicted measure of completion being at least one of a predicted number of remaining actions until the received conversation thread is resolved or a predicted number of total actions for the conversation thread to be resolved; provide, for display at a user interface, the predicted measure of completion for the received conversation thread, the predicted measure of completion being associated with the conversation thread at the user interface, and an annotation of the predicted measures of completion that is different from a remaining total number of turns as predicted; select a comment thread from a plurality of comment threads based on the predicted measure of completion; and provide, for display at the user interface, the selected comment thread as a recommend comment thread for completion by a user. 2. The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to: receive a plurality of conversation threads associated with the collaboratively developed content, the plurality of conversation threads each including a plurality of comments authored by multiple different authors; for each conversation thread of the plurality of conversation threads, generate a predicted measure of completion for the respective conversation thread, and cause the plurality of conversation threads to be displayed at the user interface based on the respective predicted measure of completion for respective conversation threads. 3. The system of claim 2 , wherein the plurality of conversation threads is displayed as being sorted according to a user indicated selection associated with the predicted measure of completion for each conversation thread. 4. The system of claim 2 , wherein the one or more hardware processors are further configured by machine-readable instructions to: generate a predicted measure of completion associated with the collaboratively developed content, the predicted measure of completion being based on the plurality of conversation threads. 5. The system of claim 1 , wherein the collaboratively developed content is at least one of source code, text of a word processing document, or slides of a presentation document. 6. The system of claim 1 , wherein the conversation thread associated with the collaboratively developed content is received at a machine learning model trained on a plurality of resolved conversation threads. 7. The system of claim 1 , wherein the predicted measure of completion is displayed at the user interface in a graphical form. 8. The system of claim 1 , wherein the predicted number of total actions for the conversation thread to be resolved is a predicted number of total comments to resolve the conversation thread. 9. The system of claim 1 , wherein the conversation thread is rearranged based on the predicted measurements of completion associated with the received conversation thread. 10. A computer-readable storage medium comprising instructions being executable by one or more processors to perform a method, the method comprising: receiving at a machine learning model trained on a plurality of resolved conversation threads, a conversation thread associated with collaboratively developed content, wherein the conversation thread includes a plurality of comments authored by multiple different authors; generating a predicted measure of completion for the received conversation thread; providing, for display at a user interface, the predicted measure of completion for the received conversation thread, the predicted measure of completion being associated with the conversation thread at the user interface, and an annotation of the predicted measures of completion that is different from a remaining total number of turns as predicted; selecting, by machine-readable instructions, a comment thread from a plurality of comment threads based on the predicted measure of completion; and providing for display at the user interface, the selected comment thread as a recommend comment thread for completion by a user. 11. The computer-readable storage medium of claim 10 , wherein the instructions cause the one or more processors to: receive a plurality of conversation threads associated with the collaboratively developed content, the plurality of conversation threads each including a plurality of comments authored by multiple different authors; for each conversation thread of the plurality of conversation threads, generate a predicted measure of completion for the respective conversation thread; and cause the plurality of conversation threads to be displayed at the user interface based on the respective predicted measure of completion for each conversation thread. 12. The computer-readable storage medium of claim 11 , wherein the plurality of conversation threads is sorted according to a user indicated selection associated with the predicted measure of completion for each conversation thread. 13. The computer-readable storage medium of claim 10 , wherein the collaboratively developed content is at least one of source code, text of a word processing document, or slides of a presentation document. 14. A method, comprising: receiving a plurality of conversation threads associated with collaboratively developed content, the plurality of conversation threads each include a plurality of comments authored by multiple different authors; for each conversation thread of the plurality of conversation threads, generating a predicted measure of completion for the respective conversation thread, the predicted measure of completion being at least one of a predicted number of remaining actions until the respective conversation thread is resolved or a predicted number of total actions for the respective conversation thread to be resolved; providing, for display at a user interface, the plurality of conversation threads to be displayed at the user interface based on the respective predicted measure of completion for each conversation thread, and an annotation of the respective predicted measures of completion that is different from a remaining total number of turns as predicted; selecting, by machine-readable instructions, a comment thread from a plurality of comment threads based on the predicted measure of completion; and providing for display at the user interface, the selected comment thread as a recommend comment thread for completion by a user. 15. The method of claim 14 , wherein the plurality of conversation threads is sorted according to a user indicated selection associated with the predicted measure of completion for each conversation thread. 16. The method of claim 15 , further comprising generating a predicted measure of completion associated with the collaboratively developed content, the predicted measure of completion being based on the plurality of conversation threads. 17. The method of claim 14 , wherein the collaboratively developed content is at least one of source code, text of a word processing document, or slides of a presentation document. 18. The method of claim 14 , wherein the plurality of conversation threads associated with the collaboratively developed content are received at a mach

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Classifications

  • G06F40/194Primary

    Calculation of difference between files · CPC title

  • Display of layout of documents; Previewing · CPC title

  • Annotation, e.g. comment data or footnotes · CPC title

  • Version control (for software G06F8/71) · CPC title

  • G06F40/35Primary

    Discourse or dialogue representation · CPC title

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What does patent US11803703B2 cover?
Systems, storage media and methods for providing information for user prioritization of tasks associated with collaboratively developed content are described. Some examples may include: receiving a conversation thread associated with collaboratively developed content, the conversation thread including a plurality of comments authored by multiple different authors, generating a predicted measure…
Who is the assignee on this patent?
Microsoft Technology Licensing Llc
What technology area does this patent fall under?
Primary CPC classification G06F40/194. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Oct 31 2023 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 4 related publications on this page (citations in our corpus or others sharing the same primary CPC).