US2024020467A1PendingUtilityA1

Collaborative communication triage assistance

Assignee: MICROSOFT TECHNOLOGY LICENSING LLCPriority: May 27, 2021Filed: Sep 26, 2023Published: Jan 18, 2024
Est. expiryMay 27, 2041(~14.8 yrs left)· nominal 20-yr term from priority
G06F 40/194G06F 40/197G06F 40/106G06F 40/169G06F 40/35G06F 40/216
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Claims

Abstract

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.

Claims

exact text as granted — not AI-modified
1 - 20 . (canceled) 
     
     
         21 . A system, comprising:
 at least one processor; and   memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising:
 obtaining a conversation thread associated with 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; 
 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; 
 identifying 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 identified comment thread as a recommend comment thread for completion by a user. 
   
     
     
         22 . The system of  claim 21 , wherein the set of operations further comprises:
 receiving a plurality of conversation threads associated with the 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, generating a predicted measure of completion for the respective conversation thread; and   causing the plurality of conversation threads to be displayed at the user interface based on the respective predicted measure of completion for respective conversation threads.   
     
     
         23 . The system of  claim 22 , 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. 
     
     
         24 . The system of  claim 22 , wherein the set of operations further comprises generating a predicted measure of completion associated with the content, the predicted measure of completion being based on the plurality of conversation threads. 
     
     
         25 . The system of  claim 21 , wherein the content is at least one of source code, text of a word processing document, or slides of a presentation document. 
     
     
         26 . The system of  claim 21 , wherein the conversation thread associated with the content is received at a machine learning model trained on a plurality of resolved conversation threads. 
     
     
         27 . The system of  claim 21 , wherein the predicted measure of completion is displayed at the user interface in a graphical form. 
     
     
         28 . The system of  claim 21 , 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. 
     
     
         29 . The system of  claim 21 , wherein the conversation thread is rearranged based on the predicted measurements of completion associated with the received conversation thread. 
     
     
         30 . A computer-readable storage medium comprising instructions being executable by one or more processors to perform a method, the method comprising:
 obtaining a conversation thread associated with content, wherein the conversation thread includes a plurality of comments authored by multiple different authors;   generating, using a machine learning model trained on a plurality of resolved conversation threads, a predicted measure of completion for the received conversation thread; and   providing, for display at a user interface, the predicted measure of completion for the 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.   
     
     
         31 . The computer-readable storage medium of  claim 30 , wherein the instructions cause the one or more processors to:
 receive a plurality of conversation threads associated with the 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.   
     
     
         32 . The computer-readable storage medium of  claim 31 , 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. 
     
     
         33 . The computer-readable storage medium of  claim 30 , wherein the content is at least one of source code, text of a word processing document, or slides of a presentation document. 
     
     
         34 . A method, comprising:
 obtaining a plurality of conversation threads associated with content, wherein 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;   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;   identifying 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 identified comment thread as a recommend comment thread for completion by a user.   
     
     
         35 . The method of  claim 34 , 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. 
     
     
         36 . The method of  claim 35 , further comprising generating a predicted measure of completion associated with the content, the predicted measure of completion being based on the plurality of conversation threads. 
     
     
         37 . The method of  claim 34 , wherein the content is at least one of source code, text of a word processing document, or slides of a presentation document. 
     
     
         38 . The method of  claim 34 , wherein the plurality of conversation threads associated with the content are received at a machine learning model trained on a plurality of resolved conversation threads. 
     
     
         39 . The method of  claim 34 , wherein the predicted number of remaining actions until the respective conversation thread is resolved is a predicted number of comments to be added to the respective conversation thread until the respective conversation thread is resolved. 
     
     
         40 . The method of  claim 34 , wherein the predicted number of total actions for the respective conversation thread to be resolved is a predicted number of total comments to resolve the respective conversation thread.

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