IP Library Granted Patent US 11,115,228
Granted Patent B2
US 11,115,228 · App. 16/526,759 · Granted Sep 7, 2021

Method, apparatus, and computer program product for individual profile telemetry discovery within a group based communication system

Inventors: Jaime DeLanghe (New York, NY); Jenna Zeigen (Brooklyn, NY); Jonathan Katzur (New York, NY); Simon Favreau-Lessard (New York, NY); Noah Weiss (New York, NY); Renaud Bourassa-Denis (New York, NY)
Assignee: Slack Technologies, Inc.
H04L12/1831G06Q10/0633H04L65/403H04L67/306
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Quick Facts
Patent No.
US 11,115,228
App. No.
16/526,759
Granted
Sep 7, 2021
Kind
B2
Abstract

Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products for discovery of individual profile telemetry within a group-based communication system.

Claims (43)

1. An apparatus comprising at least one processor and at least one memory storing computer code that, when executed by the at least one processor, causes the apparatus to:

analyze a plurality of interactions between a user account associated with a communication platform and one or more other user accounts of the communication platform to generate an attention score vector associated with the user account, the attention score vector comprising a plurality of attention scores associated with the plurality of interactions, wherein each attention score is associated with a user identifier corresponding to another user account of the one or more other user accounts;

generate, for each attention score of the plurality of attention scores, a divergence score associated with the user account based at least in part on a difference between a predicted short term attention score and an actual short term attention score, wherein the predicted short term attention score represents predicted interactions between the user account and the one or more other user accounts and the actual short term attention score represents actual interactions between the user account and the one or more other user accounts;

rank the plurality of attention scores based at least in part on the divergence score;

provide, for rendering via a client device, an interface comprising at least one of the attention score vector or a ranked list of the plurality of attention scores.

2. The apparatus of claim 1 , wherein each attention score is calculated by:

calculating a user priority score associated with a particular user identifier associated with the user account and the user identifier associated with the other user account; and

normalizing the user priority score relative to other user priority scores according to a possible attention percentage.

3. The apparatus of claim 2 , wherein the attention score represents a percentage of the possible attention percentage that the user account interacts with the other user account.

4. The apparatus of claim 1 , wherein the computer code further causes the apparatus to provide, for rendering via the client device, an attention score visual representation that is organized according to organization identifiers associated with each of the one or more other user accounts.

5. The apparatus of claim 1 , wherein the computer code further causes the apparatus to provide, for rendering via the client device, an attention score visual representation that is organized according to team identifiers associated with each of the one or more other user accounts.

6. The apparatus of claim 1 , wherein the computer code further causes the apparatus to provide, for rendering via the client device, an attention score visual representation that is organized according to channel identifiers associated with each of the one or more other user accounts.

7. The apparatus of claim 1 , wherein the computer code further causes the apparatus to provide, for rendering via the client device, an attention score visual representation comprising a grouping of attention scores associated with a subset of the one or more other user accounts that are associated with a common team identifier.

8. The apparatus of claim 7 , wherein the grouping of attention scores is presented via an attention pane.

9. The apparatus of claim 1 , wherein the computer code further causes the apparatus to provide, for rendering via the client device, an attention score visual representation comprising a grouping of attention scores associated with a subset of the one or more other user accounts that are associated with a common role type identifier.

10. The apparatus of claim 1 , wherein the attention score represents a likelihood that a first client device associated with the user account will interact via the communication platform with a second client device associated with the other user account.

11. The apparatus of claim 1 , wherein the predicted short term attention score is based at least in part on a long term attention score, and wherein the predicted short term attention score is representative of a programmatically generated expected amount of interaction between the user account and the other user account during a first network time period.

12. The apparatus of claim 11 , wherein the long term attention score is representative of an amount of interaction between the user account and the other user account during a second network time period that is different from the first network time period.

13. The apparatus of claim 1 , wherein the actual short term attention score is representative of an actual amount of interaction between the user account and the other user account during a network time period.

14. A method comprising:

analyzing a plurality of interactions between a user account associated with a communication platform and one or more other user accounts of the communication platform to generate an attention score vector associated with the user account, the attention score vector comprising a plurality of attention scores associated with the plurality of interactions, wherein each attention score is associated with a user identifier corresponding to another user account of the one or more other user accounts;

generating, for each attention score of the plurality of attention scores, a divergence score associated with the user account based at least in part on a difference between a predicted short term attention score and an actual short term attention score, wherein the predicted short term attention score represents predicted interactions between the user account and the one or more other user accounts and the actual short term attention score represents actual interactions between the user account and the one or more other user accounts;

ranking the plurality of attention scores based at least in part on the divergence score;

providing, for rendering via a client device, an interface comprising at least one of the attention score vector or a ranked list of the plurality of attention scores.

15. The method of claim 14 , further comprising:

calculating a user priority score associated with a particular user identifier associated with the user account and the user identifier associated with the other user account; and

normalizing the user priority score relative to other user priority scores according to a possible attention percentage.

16. The method of claim 15 , wherein the attention score represents a percentage of the possible attention percentage that the user account interacts with the other user account.

17. The method of claim 14 , further comprising:

providing, for rendering via the client device, an attention score visual representation.

18. The method of claim 17 , wherein the attention score visual representation is organized according to at least one of:

organization identifiers;

team identifiers;

channel identifiers; or

role type identifiers.

19. The method of claim 14 , wherein the attention score represents a likelihood that a first client device associated with the user account-will interact via the communication platform with a second client device associated with the other user account.

20. A system comprising:

one or more processors; and

one or more non-transitory computer-readable media comprising instructions that, when executed by the one or more processors, cause the system to:

analyze a plurality of interactions between a user account associated with a communication platform and one or more other user accounts of the communication platform to generate an attention score vector associated with the user account, the attention score vector comprising a plurality of attention scores associated with the plurality of interactions, wherein each attention score is associated with a user identifier corresponding to another user account of the one or more other user accounts;

generate, for each attention score of the plurality of attention scores, a divergence score associated with the user account based at least in part on a difference between a predicted short term attention score and an actual short term attention score, wherein the predicted short term attention score represents predicted interactions between the user account and the one or more other user accounts and the actual short term attention score represents actual interactions between the user account and the one or more other user accounts;

rank the plurality of attention scores based at least in part on the divergence score; and

provide, for rendering via a client device, an interface comprising at least one of the attention score vector or a ranked list of the plurality of attention scores.

Assignments (4)
MERGER Recorded Jan 11, 2023
From: SLACK TECHNOLOGIES, LLC
To: SALESFORCE.COM, INC.
Reel/Frame 062354/0073 →
CHANGE OF NAME Recorded Jan 11, 2023
From: SALESFORCE.COM, INC.
To: SALESFORCE, INC.
Reel/Frame 062354/0100 →
MERGER AND CHANGE OF NAME Recorded Oct 1, 2021
From: SLACK TECHNOLOGIES, INC.; SLACK TECHNOLOGIES, LLC
To: SLACK TECHNOLOGIES, LLC
Reel/Frame 057683/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 8, 2019
From: DELANGHE, JAIME; ZEIGEN, JENNA; KATZUR, JONATHAN; FAVREAU-LESSARD, SIMON; WEISS, NOAH; BOURASSA-DENIS, RENAUD
To: SLACK TECHNOLOGIES, INC.
Reel/Frame 050657/0342 →
Continuity (2)
Provisional Application 62712013 · Jul 30, 2018
Related Publication 20200036548A1 · Jan 30, 2020
Cited By (2)
US 12,309,460 US 12,647,635