Automatically suggesting groups based on past user interaction

• US 9,299,060 B2
• Filed: 10/12/2012
• Issued: 03/29/2016
• Est. Priority Date: 10/12/2012
• Status: Expired due to Fees

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Panzer, John
• Primary Examiner(s): Gillis, Brian J
• Assistant Examiner(s): Lee, Gil H.
• Application Number:
  US13/651,199
• Publication Number:
  US 20140108562A1
• Time in Patent Office: 1,264 Days
• Field of Search: 707/748, 707/749, 707/751, 707/E17.032, 709/203, 709/204, 709/206, 715/753
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 51/02 using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04L 51/56 Unified messaging, e.g. interactions between e-mail, instant messaging or converged IP messaging [CPM]

Abstract

An example implementation includes processing message-related information of a first user for a cluster of related users and determining interaction levels for the cluster of related users. The interaction levels describe a level of interaction between the first user and the related users of the cluster. The users of the cluster are ranked based on the interaction levels and a group suggestion is generated suggesting a group be created on a social networking service based on the ranking of the cluster of related users. The group suggestion is sent to the first user for presentation and a response is received from the first user including user input provided in response to the group suggestion being sent. A group of users is created on the social networking service based on the response.

Claims

1. A computer-implemented method comprising:

aggregating message-related information of a first user from a plurality of electronic messages associated with the first user;

identifying a cluster of related users based on the aggregated message-related information of the first user and conversations included in the plurality of electronic messages in which the cluster of related users discussed a similar subject matter;

determining interaction levels for the cluster of related users, the interaction levels describing a level of interaction between the first user and related users of the cluster of related users;

ranking the cluster of related users based on the interaction levels;

determining a group scope based on the interaction levels;

generating a group name based on the similar subject matter;

generating a group suggestion suggesting a group be created on a social networking service based on the ranking of the cluster of related users, the group suggestion including the determined group scope and the generated group name;

determining that the first user is participating in at least one of the conversations;

responsive to determining that the first user is participating in the at least one of the conversations, sending the group suggestion to the first user for presentation;

receiving a response from the first user including user input provided in response to the sending of the group suggestion; and

creating the group of users on the social networking service based on the response.

2. The computer-implemented method of claim 1, wherein the message-related information describes a plurality of electronic messages and the processing of the message-related information includes processing the plurality of electronic messages for one or more past interactions between the first user and a plurality of other users and identifying the cluster of related users based on the one or more past interactions.

3. The computer-implemented method of claim 2, wherein the message-related information includes conversational content and user data associated with the plurality of electronic messages and the processing of the message-related information includes processing the conversational content and the user data for the one or more past interactions.

4. The computer-implemented method of claim 1, comprising:

receiving a group request from the first user requesting the group suggestion be provided; and

aggregating the message-related information from one or more information sources storing electronic messages of the first user.

5. The computer-implemented method of claim 4, wherein the electronic messages include one or more of electronic mail messages, SMS/MMS messages, instant messages, social network posts, social network notifications, and micro blog posts.

6. The computer-implemented method of claim 1, comprising:

processing the message-related information for a group name, wherein the generating of the group suggestion is based on the group name.

7. The computer-implemented method of claim 1, wherein the generating of the group suggestion further includes generating the group suggestion to reflect the ranking of the related users of the cluster.

8. The computer-implemented method of claim 1, comprising:

processing the user input included in the response from the first user for one or more revisions to the group suggestion;

generating accuracy improvement data based on the one or more revisions; and

generating a second group suggestion suggesting a second group be created on the social networking service based on the message-related information and the accuracy improvement data.

9. A computer program product comprising a non-transitory computer-usable medium including a computer-readable program, wherein the computer-readable program, when executed on a computer, causes the computer to:

aggregate message-related information of a first user from a plurality of electronic messages associated with the first user;

identify a cluster of related users based on the aggregated message-related information of the first user and conversations included in the plurality of electronic messages in which the cluster of related users discussed a similar subject matter;

determine interaction levels for the cluster of related users, the interaction levels describing a level of interaction between the first user and related users of the cluster of related users;

rank the cluster of related users based on the interaction levels;

determine a group scope based on the interaction levels;

generate a group name based on the similar subject matter;

generate a group suggestion suggesting a group be created on a social networking service based on the ranking of the cluster of related users, the group suggestion including the determined group scope and the generated group name;

determine that the first user is participating in at least one of the conversations;

responsive to determining that the first user is participating in the at least one of the conversations, send the group suggestion to the first user for presentation;

receive a response from the first user including user input provided in response to the group suggestion being sent; and

create the group of users on the social networking service based on the response.

10. The computer program product of claim 9, wherein the message-related information describes a plurality of electronic messages and to process the message-related information includes processing the plurality of electronic messages for one or more past interactions between the first user and a plurality of other users and identifying the cluster of related users based on the one or more past interactions.

11. The computer program product of claim 10, wherein the message-related information includes conversational content and user data associated with the plurality of electronic messages and to process the message-related information further includes processing the conversational content and the user data for the one or more past interactions.

12. The computer program product of claim 9, wherein the computer-readable program further causes the computer to:

receive a group request from the first user requesting the group suggestion be provided; and

aggregate the message-related information from one or more information sources storing electronic messages of the first user.

13. The computer program product of claim 12, wherein the electronic messages include one or more of electronic mail messages, SMS/MMS messages, instant messages, social network posts, social network notifications, and micro blog posts.

14. The computer program product of claim 9, wherein the computer-readable program further causes the computer to:

process the message-related information for a group name, wherein to generate the group suggestion includes generating the group suggestion based on the group name.

15. The computer program product of claim 9, wherein to generate the group suggestion further includes generating the group suggestion to reflect the ranking of the related users of the cluster.

16. The computer program product of claim 9, wherein the computer-readable program further causes the computer to:

process the user input included in the response from the first user for one or more revisions to the group suggestion;

generate accuracy improvement data based on the one or more revisions; and

generate a second group suggestion suggesting a second group be created on the social networking service based on the message-related information and the accuracy improvement data.

17. A system comprising:

a processor; and

a memory storing instructions that, when executed, cause the system to;

aggregate message-related information of a first user from a plurality of electronic messages associated with the first user;

identify a cluster of related users based on the aggregated message-related information of the first user and conversations included in the plurality of electronic messages in which the cluster of related users discussed a similar subject matter;

determine interaction levels for the cluster of related users, the interaction levels describing a level of interaction between the first user and related users of the cluster of related users;

rank the cluster of related users based on the interaction levels;

determine a group scope based on the interaction levels;

generate a group name based on the similar subject matter;

generate a group suggestion suggesting a group be created on a social networking service based on the ranking of the cluster of related users, the group suggestion including the determined group scope and the generated group name;

determine that the first user is participating in at least one of the conversations;

responsive to determining that the first user is participating in the at least one of the conversations, send the group suggestion to the first user for presentation;

receive a response from the first user including user input provided in response to the group suggestion being sent; and

create the group of users on the social networking service based on the response.

18. The system of claim 17, wherein the message-related information describes a plurality of electronic messages and to process the message-related information includes processing the plurality of electronic messages for one or more past interactions between the first user and a plurality of other users and identifying the cluster of related users based on the one or more past interactions.

19. The system of claim 18, wherein the message-related information includes conversational content and user data associated with the plurality of electronic messages and to process the message-related information further includes processing the conversational content and the user data for the one or more past interactions.

20. The system of claim 17, wherein the instructions further cause the system to receive a group request from the first user requesting the group suggestion be provided and aggregate the message-related information from one or more information sources storing electronic messages of the first user.

21. The system of claim 20, wherein the electronic messages include one or more of electronic mail messages, SMS/MMS messages, instant messages, social network posts, social network notifications, and micro blog posts.

22. The system of claim 17, wherein the instructions further cause the system to process the message-related information for a group name, wherein to generate the group suggestion includes generating the group suggestion based on the group name.

23. The system of claim 17, wherein to generate the group suggestion further includes generating the group suggestion to reflect the ranking of the related users of the cluster.

24. The system of claim 17, wherein the instructions further cause the system to process the user input included in the response from the first user for one or more revisions to the group suggestion, generate accuracy improvement data based on the one or more revisions, and generate a second group suggestion suggesting a second group be created on the social networking service based on the message-related information and the accuracy improvement data.