Engagement signal generation and analysis
US-2022351034-A1 · Nov 3, 2022 · US
US12217171B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12217171-B2 |
| Application number | US-202117245948-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 30, 2021 |
| Priority date | Apr 30, 2021 |
| Publication date | Feb 4, 2025 |
| Grant date | Feb 4, 2025 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
Engagement signals may be generated and analyzed based on user interactions with documents, particularly in a collaboration environment. The user interactions may generate raw collaboration signals that may be received and processed into cleaned collaboration signals. For example, noise may be removed from the raw collaboration signals to generate the cleaned collaboration signals. The cleaned collaboration signals may be grouped into engagement signals, where each engagement signal represents an individual event or engagement event of the user with the document. The grouping may be based on boundary signals, time frames, and/or any other reasonable limiting element. Each of the engagement signals may be classified into one of several engagement types based on the cleaned collaboration signals in the engagement signal. The engagement signals may then be analyzed to make determinations, recommendations, or the like regarding one or more users of the document, the document content, or the like.
Opening claim text (preview).
What is claimed is: 1. A computer-implemented method for generating and analyzing engagement signals, the method comprising: for each user of a plurality of users: receiving raw collaboration signals generated based on the respective user interacting with a document, processing the raw collaboration signals into cleaned collaboration signals, grouping the cleaned collaboration signals into engagement signals, each engagement signal representing an individual event, wherein the grouping comprises identifying boundary signals for the individual events with a neural network configured to identify the boundary signals, the identifying comprising: ingesting, by the neural network, the cleaned collaboration signals; and outputting, from the neural network, the boundary signals that indicate a beginning and end of the individual events, and classifying each of the engagement signals into one of a plurality of engagement types based on the cleaned collaboration signals in the respective engagement signal; generating a collaboration insight comprising collaboration information generated at least in part from the engagement signals of a first user of the plurality of users; and causing to display, on a display of a computing device of a second user of the plurality of users, a graphical user interface comprising the collaboration insight. 2. The computer-implemented method of claim 1 , wherein the raw collaboration signals comprise at least one of document open signals, window minimize signals, window focus signals, document close signals, window maximize signals, input activity signals, or a combination thereof. 3. The computer-implemented method of claim 1 , wherein processing the raw collaboration signals into the cleaned collaboration signals comprises aggregating the raw collaboration signals to remove noise. 4. The computer-implemented method of claim 1 , wherein the grouping the cleaned collaboration signals into the engagement signals comprises: combining the cleaned collaboration signals occurring between the boundary signals into the respective engagement signal. 5. The computer-implemented method of claim 1 , further comprising: analyzing the classified engagement signals of the plurality of users; and classifying content of the document based at least in part on the analyzing. 6. The computer-implemented method of claim 1 , wherein the classifying each of the engagement signals into the one of the plurality of engagement types comprises: providing each of the engagement signals into an intelligence classifier; and receiving an engagement type as output from the intelligence classifier for each of the engagement signals. 7. The computer-implemented method of claim 1 , wherein the engagement types comprise editing, viewing, reviewing, and authoring. 8. The computer-implemented method of claim 1 , further comprising: assigning a collaboration role to the first user for the document based on the classified engagement signals. 9. The computer-implemented method of claim 1 , further comprising: providing recommendations to a contributor of the document based on analyzing the classified engagement signals of the plurality of users of the document. 10. The computer-implemented method of claim 1 , further comprising: sending a notification of an action related to the document to one of the plurality of users of the document based at least in part on the classified engagement signals. 11. A system comprising: one or more processors; and a memory having stored thereon instructions that, upon execution by the one or more processors, cause the one or more processors to: for each user of a plurality of users: receive raw collaboration signals generated based on the respective user interacting with a document; process the raw collaboration signals into cleaned collaboration signals; group the cleaned collaboration signals into engagement signals, each engagement signal representing an individual event, wherein the instructions to group comprises further instructions to identify boundary signals for the individual events with a neural network configured to identify the boundary signals, the instructions to identify comprising further instructions to: ingest, by the neural network, the cleaned collaboration signals, and output, from the neural network, the boundary signals that indicate a beginning and end of the individual events; and classify each of the engagement signals into one of a plurality of engagement types based on the cleaned collaboration signals in the respective engagement signal, generate a collaboration insight comprising collaboration information generated at least in part from the engagement signals of a first user of the plurality of users, and cause to display, on a display of a computing device of a second user of the plurality of users, a graphical user interface comprising the collaboration insight. 12. The system of claim 11 , wherein the raw collaboration signals comprise at least one of document open signals, window minimize signals, window focus signals, document close signals, window maximize signals, input activity signals, or a combination thereof. 13. The system of claim 11 , wherein the instructions to process the raw collaboration signals into the cleaned collaboration signals comprises instructions that, upon execution by the one or more processors, cause the one or more processors to aggregate the raw collaboration signals to remove noise. 14. The system of claim 11 , wherein the instructions to group the cleaned collaboration signals into the engagement signals comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to: combine the cleaned collaboration signals occurring between the boundary signals into the respective engagement signal. 15. The system of claim 11 , wherein the instructions comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to: analyze the classified engagement signals of the plurality of users; and classify content of the document based at least in part on the analysis. 16. The system of claim 11 , wherein the instructions to classify each of the engagement signals into the one of the plurality of engagement types comprises instructions that, upon execution by the one or more processors, cause the one or more processors to: provide each of the engagement signals into an intelligence classifier; and receive an engagement type as output from the intelligence classifier for each of the engagement signals. 17. The system of claim 11 , wherein the engagement types comprise editing, viewing, reviewing, and authoring. 18. The system of claim 11 , wherein the instructions comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to: assign a collaboration role to the first user for the document based on the classified engagement signals. 19. The system of claim 11 , wherein the instructions comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to: provide recommendations to a contributor of the document based on analyzing the classified engagement signals of the plurality of users of the document. 20. The system of claim 11 , wherein the instructions comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to: send a notification o
Related publications grouped by family.
Answers are generated from the same data shown on this page.