Aggregating enterprise graph content around user-generated topics

Patent metadata

Field	Value
Publication number	US-11836653-B2
Application number	US-202016895056-A
Country	US
Kind code	B2
Filing date	Jun 8, 2020
Priority date	Mar 3, 2014
Publication date	Dec 5, 2023
Grant date	Dec 5, 2023

Abstract

Aggregation of content based on user-generated topics is provided. Users may associate one or more topics with content items stored across various workloads and repositories. A topic may be a word or phrase of the user's choice, and may be utilized for discoverability of information and aggregation of content items. Topics and content items associated with topics may be acted on (e.g., a user may add or delete topics to associate with a content item, associate or disassociate content items with a topic, embed a set of content items or a stream of content items associated with a topic into other experiences, follow topics, etc.). Content items identified as related to a specific topic may be automatically suggested as possible content items of interest to the user. Additionally, when a user follows a topic, the user may be notified of any changes that occur to the topic.

First claim

We claim:

1. A computer-implemented method for aggregating content items, the method comprising:
receiving an indication of a selected topic associated with a user, the selected topic being tracked in a graph;
based on the selected topic, generating, by an analytics engine, a set of suggested content items, wherein each suggested content item of the set of suggested content items is not associated in the graph with the selected topic and is associated in the graph with the user;
presenting one or more of the suggested content items as suggestions to associate with the selected topic;
receiving a selection of a suggested content item; and
generating an association between the selected topic and the suggested content item.

2. The method of claim 1 , further comprising, in response to the received selection, presenting a display of content items associated with the selected topic, wherein the display comprises the suggested content item.

3. The method of claim 1 , wherein generating the set of suggested content items comprises:
identifying an inferred edge in the graph, wherein the inferred edge is between a first content item that is not associated with the selected topic and either:
a second content item that is associated with the selected topic; or
the selected topic; and

based on identifying the inferred edge, adding the first content item to the set of suggested content items.

4. The method of claim 3 , wherein the inferred edge was generated based at least in part on a determination that a user associated with the first content item is associated with the second content item.

5. The method of claim 1 , wherein the set of suggested content items is generated based at least in part on text similarity, vocabulary similarity, semantics similarity, or topic similarity.

6. The method of claim 1 , wherein generating the association further comprises generating a notification that the suggested content item is associated with the selected topic.

7. The method of claim 1 , further comprising presenting at least one content item that is associated with the selected topic.

8. A system for aggregating content items, the system comprising:
a processor; and
memory storing instructions that, when executed by the processor, cause the system to perform a set of operations comprising:
receiving an indication of a selected topic associated with a user, the selected topic being tracked in a graph;
based on the selected topic, generating, by an analytics engine, a set of suggested content items, wherein each suggested content item of the set of suggested content items is not associated in the graph with the selected topic and is associated in the graph with the user;
presenting one or more of the suggested content items as suggestions to associate with the selected topic;
receiving a selection of a suggested content item; and
generating an association between the selected topic and the suggested content item.

9. The system of claim 8 , wherein the operations further comprise, in response to the received selection, presenting a display of content items associated with the selected topic, wherein the display comprises the suggested content item.

10. The system of claim 8 , wherein generating the set of suggested content items comprises:
identifying an inferred edge in the graph, wherein the inferred edge is between a first content item that is not associated with the selected topic and either:
a second content item that is associated with the selected topic; or
the selected topic; and

based on identifying the inferred edge, adding the first content item to the set of suggested content items.

11. The system of claim 10 , wherein the inferred edge was generated based at least in part on a determination that a user associated with the first content item is associated with the second content item.

12. The system of claim 8 , wherein the set of suggested content items is generated based at least in part on text similarity, vocabulary similarity, semantics similarity, or topic similarity.

13. The system of claim 8 , wherein generating the association further comprises generating a notification that the suggested content item is associated with the selected topic.

14. The system of claim 8 , wherein the operations further comprise presenting at least one content item that is associated with the selected topic.

15. A computer-implemented method for aggregating content items, the method comprising:
receiving an indication of a selected topic tracked in a graph associated with a user, the selected topic being;
based on the selected topic, generating, by an analytics engine, a set of suggested content items, wherein each suggested content item of the set of suggested content items is not associated in the graph with the selected topic and is associated in the graph with the user;
presenting one or more of the suggested content items as suggestions to associate with the selected topic;
receiving a selection of a suggested content item;
in response to the received selection: presenting a display of content items associated with the selected topic, wherein the display comprises the suggested content item; and
generating an association between the selected topic and the suggested content item.

16. The computer-implemented method of claim 15 , wherein generating the set of suggested content items comprises:
identifying an inferred edge in the graph, wherein the inferred edge is between a first content item that is not associated with the selected topic and either:
a second content item that is associated with the selected topic; or
the selected topic; and

based on identifying the inferred edge, adding the first content item to the set of suggested content items.

17. The computer-implemented method of claim 16 , wherein the inferred edge was generated based at least in part on a determination that a user associated with the first content item is associated with the second content item.

18. The computer-implemented method of claim 15 , wherein the set of suggested content items is generated based at least in part on text similarity, vocabulary similarity, semantics similarity, or topic similarity.

19. The computer-implemented method of claim 15 , wherein generating the association further comprises generating a notification that the suggested content item is associated with the selected topic.

20. The computer-implemented method of claim 15 , further comprising presenting at least one content item that is associated with the selected topic.

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Stickler Joshua
• Kehler Christopher
• Meyerzon Dmitriy
• Poznanski Victor
• Kuppusamy Ashok
• Melnychuk Oleg
• Little Charles Reeves

Classifications

• G06Q10/06 Primary

  Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling · CPC title

• G06Q30/02

  Marketing; Price estimation or determination; Fundraising · CPC title

• G06F8/34

  Graphical or visual programming · CPC title

• G11B27/034

  on discs (G11B27/036, G11B27/038 take precedence) · CPC title