Systems and methods for generating location-based group recommendations

• US 8,463,295 B1
• Filed: 12/07/2011
• Issued: 06/11/2013
• Est. Priority Date: 12/07/2011
• Status: Active Grant

• Current Assignee: PayPal, Inc. (PayPal Holdings, Inc.)
• Original Assignee: eBay Inc.
• Inventors: Nakamura, Masumi, Caralis, Jim, Kogan, Nataly, Mastroianni, Michael, Sundram, Jason
• Primary Examiner(s): PATEL, MAHENDRA R
• Application Number:
  US13/313,681
• Publication Number:
  US 20130150086A1
• Time in Patent Office: 552 Days
• Field of Search: 455/456.3, 455/561, 455/456.1, 455/422, 455/440, 455/436, 455/414.2, 455/456.5, 341/94, 705/26.1, 705/14.53, 705/14.54, 705/5, 705/319, 705/1.1, 705/14.58, 323/205, 375/E7.257, 375/E7.129, 725/105, 725/131, 725/32, 707/723
• US Class Current: 455/456.3
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

Methods and systems for generating location-aware group recommendations are discussed. For example, a method can include operations for receiving a group recommendation request, accessing user profile data associated with members of the group, and generating a group recommendation. The group recommendation request can be received at a network-based system and include identification of a first and second user as well as information identifying a current location associated with the first and second users. Accessing the user profile information can include accessing user profile information for both the first and second users. The group recommendation can be generated based on the current location data and a combination of at least a portion of the user profile data from the first and second users.

Claims

1. A method for providing location-aware group recommendations, the method comprising:

receiving, at a network-based system, a group recommendation request from a mobile device associated with a first user, the group recommendation request including identification of a second user, a relationship indicator that includes information describing a relationship between the first user and the second user, and information identifying a current location associated with at least one of the first and second users;

accessing, using one or more processors within the network-based system, user profile data associated with the first user and the second user; and

generating, using one or more processors within the network-based system, a predictive common recommendation, the predictive common recommendation generated based on,

calculating, using one or more processors within the network-based system, a first place graph for the first user and a second place graph for the second user based on the current location and a combination of a portion of the user profile data associated with the first user and a portion of the user profile data associated with the second user,

merging the first place graph and second place graph to create a third place graph, and

traversing the third place graph to generate the predictive common recommendation; and

wherein the predictive common recommendation includes a recommendation for a local establishment or event venue.

2. The method of claim 1, wherein the accessing the user profile data includes using the relationship indicator to locate information associated with the second user.

3. The method of claim 1, wherein the relationship indicator indicates that the second user is part of a social graph associated with the first user.

4. The method of claim 1, wherein the relationship indicator indicates that the second user exchanged user profile data directly with the first user.

5. The method of claim 4, wherein the relationship indicator indicates that the first user and the second user exchanged user profile data via mobile devices associated with the first user and the second user.

6. The method of claim 4, wherein the accessing user profile data associated with the second user includes receiving user profile data associated with the second user with the group recommendation request after the first user received the user profile data from the second user.

7. The method of claim 1, wherein calculating the first place graph or second place graph includes:

accessing user profile data for a user, the user profile data including a first plurality of places with associated interaction history recorded within the user profile data;

extracting a feature matrix from the first plurality of places;

accessing place data for a second plurality of places within the current location; and

projecting the feature matrix from the first plurality of places onto the second plurality of places within the current location.

8. A non-transitory machine-readable storage medium comprising instructions which, when performed by a network-based system, cause the system to:

receive, at the network-based system, a group recommendation request associated with a first user, the group recommendation request including identification of a second user, a relationship indicator that includes information describing a relationship between the first user and the second user, and information identifying a current location associated with at least one of the first and second users;

access, using one or more processors within the network-based system, user profile data associated with the first user and the second user; and

generate, using one or more processors within the network-based system, a predictive common recommendation, the predictive common recommendation generated based on,

calculating a first place graph for the first user and a second place graph for the second user based on the current location and a combination of a portion of the user profile data associated with the first user and a portion of the user profile data associated with the second user,

merging the first place graph and second place graph to create a third place graph, and

traversing the third place graph to generate the predictive common recommendation; and

wherein the predictive common recommendation includes a recommendation for a local establishment or event venue.

9. A method of providing a location-aware group recommendation on a mobile device, the method comprising:

identifying, with the mobile device, a second user to be associated with the location-aware group recommendation;

generating a group recommendation request on the mobile device, the group recommendation request including identification of a first user associated with the mobile device, identification of the second user, and a current location associated with the mobile device or the second user;

transmitting, from the mobile device, the group recommendation request to a network-based recommendation engine; and

receiving, at the mobile device, a group recommendation, the group recommendation generated based on,

calculating a first place graph for the first user and a second place graph for the second user based on the current location and a combination of a portion of the user profile data associated with the first user and a portion of the user profile data associated with the second user,

merging the first place graph and second place graph to create a third place graph, and

traversing the third place graph to generate the predictive common recommendation; and

wherein the predictive common recommendation includes a recommendation for a local establishment or event venue.

10. The method of claim 9, wherein the identifying the second user includes detecting the selection of the second user from a plurality of users, the plurality of users associated with the first user through a social graph.

11. The method of claim 9, wherein the identifying the second user includes detecting a second mobile device associated with the second user in proximity to the mobile device.

12. The method of claim 11, wherein the identifying the second user includes validating selection of the second user after the mobile device detects presence of a second mobile device associated with the second user.

13. The method of claim 11, wherein the detecting the second mobile device includes detecting the second mobile device over a protocol consistent with any one of the following:

WiFi (IEEE 802.11 series of local-area networking protocols);

near-field communication (NFC);

bluetooth; and

cellular wireless data networks including CDMA, GSM, GPRS, EDGE, EVDO, WiMax, and LTE based networks.

14. The method of claim 9, wherein the identifying the second user includes detecting one of the following:

a check-in, on the mobile device, at the current location; and

a selection of the second user from a plurality of users, the plurality of users all also checked-in at the current location within a pre-defined period of time.

15. The method of claim 9, further comprising:

receiving user profile data associated with the second user on the mobile device; and

wherein transmitting the group recommendation request includes transmitting the user profile data associated with the second user.

16. The method of claim 9, wherein the identifying the second user includes determining a relationship between the first user and the second user;

and

wherein the receiving the group recommendation includes receiving the group recommendation generated based at least in part on the relationship between the first user and the second user.

17. The method of claim 16, wherein determining a relationship between the first user and the second user includes one of the following types of relationships:

a social relationship as indicated by a social graph associated with the first user, the social graph extracted from a social network;

a business relationship as selected by the first user; and

a new relationship as indicated by the lack of previous social or business relationships between the first user and the second user.