SOCIAL WHERE NEXT SUGGESTION

• US 20150106366A1
• Filed: 10/15/2013
• Published: 04/16/2015
• Est. Priority Date: 10/15/2013
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Stuttle, Matthew Nicholas, Drner, Sebastian, Gherghina, Alexandra
• Granted Patent: US 9,558,242 B2
• Time in Patent Office: Days
• US Class Current: 707/732
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/90324 using system suggestions
• CPC Class Codes: G06Q 30/0259 based on store location
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 30/0267 Wireless devices
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A group recommendation provides end users in a social group a set of recommended destinations based on the combined personal preferences of the members of the social group. Members of a social group are identified using a combination of location based signals and social graph information in response to receiving a recommendation request. The group recommendation may be determined by combining the personal preferences associated with each member of the group into a master preference profile. Alternatively, the group recommendation may be determined by first calculating an individual recommendation list for each member of the social group and then calculating a composite score for each recommendation on the individual recommendation lists.

Claims

1. A computer-implemented method to provide destination recommendations to social groups, comprising:

identifying, by one or more computing devices, a preliminary social group based on one or more location signals received from one or more remote computing device, wherein the one or more location signals indicate that the one or more remote computing devices are within a defined proximity threshold;

identifying, by the one or more computing devices, those members associated with the one or more remote computing devices of the preliminary social group that meet a social connection threshold with the requesting user to define a final social group;

generating, by the one or more computing devices, a ranked group recommendation list for the final social group, the ranked group recommendation list comprising a ranked list of suggested destinations for the group based at least in part on personal preference profiles of each member of the final social group; and

displaying, by the one or more computing devices, the ranked social group recommendation on the first remote computing device.

2. The method of claim 1, further comprising receiving, by the one or more computing devices associated with the destination recommendation system, a recommendation request from a first remote computing device associated with a requesting user.

3. The method of claim 1, wherein generating a ranked social group recommendation list comprises:

determining, by the one or more computing devices, a ranked individual recommendation list for each member of the final social group, the ranked individual recommendation list for each particular member comprising one or more ranked destination recommendations based at least in part on a personal preference profile of the particular member;

identifying, by the one or more computing devices, a set of common recommendations that appear in more than one individual recommendation list;

determining, by the one or more computing devices, a composite score for each identified common recommendation, wherein the composite score is based at least in part on the ranking of each common recommendation in the corresponding individual recommendation lists; and

generating, by the one or more computing devices, the ranked group recommendation list based on the composite score assigned to each identified common recommendation.

4. The method of claim 1, wherein generating a ranked group recommendation list comprises:

generating, by the one or more computing devices, a master preference profile for the final social group based at least in part on a combination of the personal preference profiles of each member of the final social group; and

generating, by the one or more computing devices, a ranked social group recommendation list based at least in part on the master preference profile.

5. The method of claim 1, further comprising:

communicating, by the one or more computing devices, a social group confirmation request to the first remote computing device prior to generating the ranked social group recommendation list, the social group confirmation request identifying potential members for the social group; and

receiving, by the one or more computing devices, a social group confirmation from the first remote computing device confirming which of the potential members to include in the final social group.

6. The method of claim 1, wherein the one or more location signals comprises a check-in location signal received from a remote computing device associated with a member of the final social group.

7. The method of claim 1, wherein the one or more location signals comprises a tag signal.

8. The method of claim 7, wherein the tag signal is associated with the check-in signal of the first member of the social group, or a photo taken within the proximity threshold.

9. A computer program product, comprising:

a non-transitory computer-executable storage device having computer-executable program instructions embodied thereon that when executed by a computer cause the computer to provide destination recommendations to social groups, the computer-executable program instructions comprising;

computer-executable program instructions to receive a recommendation request from a remote computing device associated with a requesting user;

computer-executable program instructions to identify one or more users that are within a social connection threshold with the requesting user on a social graph of the requesting user;

computer-executable program instructions to identify the one or more users that are within the social connection threshold that are also within a defined proximity threshold based on a location-based signal received from one or more remote computing device associated with the one or more users to define a final social group;

computer-executable program instructions to generate a ranked group recommendation list for the social group, the ranked group recommendation list comprising a ranked list of suggested destinations for the group based at least in part on the personal preferences of each member of the social group; and

computer-executable program instructions to display the ranked social group recommendation on the first remote computing device.

10. The computer program product of claim 9, wherein generating a ranked social group recommendation list comprises:

computer-executable program instructions to determine a ranked individual recommendation list for each member of the final social group, the ranked individual recommendation list for each particular member comprising one or more ranked destination recommendations based at least in part on a personal preference profile of the particular member;

computer-executable program instructions to identify a set of common recommendations that appear in more than one individual recommendation list;

computer-executable program instructions to determine a composite score for each identified common recommendation, wherein the composite score is based at least in part on the ranking of each common recommendation in the corresponding individual recommendation lists; and

computer-executable program instructions to generate the ranked group recommendation list based on the composite score assigned to each identified common recommendation.

11. The computer program product of claim 9, wherein generating a ranked group recommendation list comprises:

computer-executable program instructions to generate a master preference profile for the social group based at least in part on the combined personal preference profiles of each member of the social group; and

computer-executable program instructions to generate a ranked social group recommendation list based at least in part on the master preference profile.

12. The computer program product of claim 9, wherein the one or more location-based signals is a check-in location signal received from a remote computing device associated with a member of the social group.

13. The computer program product of claim 9, wherein the one or more location signals is a tag signal.

14. The computer program product of claim 13, wherein the tag signal is associated a check-in signal or a photo taken within the defined proximity threshold.

15. A system to provide destination recommendations to social groups, comprising:

a storage device; and

a processor communicatively coupled to the storage device, wherein the processor executes application code instructions that are stored in the storage device to cause the system to;

identify a preliminary social group based on one or more location-based signals received from a first remote computing device, other remote computing devices, or a combination thereof;

identify those members of the preliminary social group that meet a social connection threshold with the requesting user to define a final social group;

generate a ranked group recommendation list for the final social group, the ranked group recommendation list comprising a ranked list of suggested destinations for the group based at least in part on the personal preferences of each member of the final social group; and

display the ranked social group recommendation on the first remote computing device.

16. The system of claim 15, wherein the one or more location signals indicates that each member of the social group is within a defined proximity threshold to the first remote computing device.

17. The system of claim 15, wherein generating a ranked group recommendation list further comprises executing application code instructions that cause the system to:

determine a ranked individual recommendation list for each member of the final social group, the ranked individual recommendation list for each particular member comprising one or more ranked destination recommendations based at least in part on a personal preference profile of the particular member;

identify a set of common recommendations that appear in more than one individual recommendation list;

determine a composite score for each identified common recommendation, wherein the composite score is based at least in part on the ranking of each common recommendation in the corresponding individual recommendation lists; and

generate the ranked group recommendation list based on the composite score assigned to each identified common recommendation.

18. The system of claim 15, wherein generating a ranked group recommendation list further comprises executing application code instructions that cause the system to:

generate a master preference profile for the final social group based at least in part on the combined personal preference profiles of each member of the social group; and

generate a ranked social group recommendation list based at least in part on the master preference profile.

19. The system of claim 15, wherein the one or more location signals is a check-in location signal received from a remote computing device associated with a member of the social group.

20. The system of claim 15, wherein the one or more location signals is a tag signal.

21. The system of claim 20, wherein the tag signal is associated with a check-in signal, or a photo taken within the defined proximity threshold.