System and Method for Group Recommendation of Objects Using User Comparisons of Object Characteristics

• US 20150066915A1
• Filed: 12/12/2012
• Published: 03/05/2015
• Est. Priority Date: 11/20/2012
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Golder, Scott, Chi, Ed Huai-Hsin, Huffaker, David Andrew, Kossinets, Gueorgi
• Application Number:
  US13/712,046
• Publication Number:
  US 20150066915A1
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

Systems and methods for determining a group recommendation of an object, such as a restaurant, movie, or other object, from a plurality of candidate objects based on user comparisons of characteristic traits of the candidate objects are provided. In particular, keywords associated with characteristic traits are identified. The keywords are then presented to members of the group as a series of selection queries. The selection queries require a user to select or rank the keywords based on user preferences. The responses to the selection queries are used to generate a ranking score for each of the plurality of candidate objects and to select one or more of the candidate objects to recommend to the group.

Claims

1. A computer-implemented method of providing a recommendation to a group of at least one object from a plurality of candidate objects, the method comprising:

identifying, by one or more computing devices, a plurality of keywords associated with the plurality of candidate objects from at least one data store storing information associated with the plurality of candidate objects;

generating, by the one or more computing devices, a plurality of selection queries, each selection query presenting two or more keywords, each keyword being identified for inclusion in the selection query based on a number of candidate objects associated with the keyword in the at least one data store;

providing, by the one or more computing devices, the plurality of selection queries to each of a plurality of users in the group, each of the plurality of selection queries requiring a user to select one or more of the plurality of keywords based on user preferences,

receiving, by the one or more computing devices, a response to each of to the plurality of selection queries from the plurality of users; and

generating, by the one or more computing devices, a recommendation for the plurality of candidate objects based on the responses to the plurality of selection queries.

2. The computer-implemented method of claim 1, wherein the method further comprises:

initiating, at the one or more computing devices, a group decision session; and

inviting, by the one or more computing devices, the plurality of users to participate in the group decision session.

3. The computer-implemented method of claim 1, wherein the recommendation is generated based on a ranking score generated for each of the plurality of candidate objects.

4. The computer-implemented method of claim 1, wherein each of the plurality of keywords is associated with a characteristic trait of at least one of the plurality of candidate objects.

5. The computer-implemented method of claim 1, wherein at least one of the plurality of selection queries requires the user to make a pairwise decision between two keywords.

6. The computer-implemented method of claim 1, wherein at least one of the plurality of selection queries requires the user to rank a plurality of keywords.

7. The computer-implemented method of claim 3, wherein generating a ranking score for each of the plurality of candidate objects based on the responses to the plurality of selection queries, comprises:

assigning by the one or more computing devices, a point value to a keyword based on the responses to the plurality of selection queries;

assigning, by the one or more computing devices, the point value to at least one candidate object associated with the keyword; and

summing, by the one or more computing devices, the point values assigned to each candidate object.

8. The computer-implemented method of claim 7, wherein the point value is assigned to the keyword based on a selection of the keyword in response to one of the plurality of selection queries.

9. The computer-implemented method of claim 7, wherein the point value is assigned to the keyword based on a ranking of the keyword provided in response to one of the plurality of selection queries.

10. The computer-implemented method of claim 1, wherein the method comprises:

assigning, by the one or more computing devices, a weighting value to one of the plurality of keywords based on the number of candidate objects associated with the keyword; and

selecting, by the one or more computing devices, the keyword for one of the plurality of selection queries based on the weighting value assigned to the keyword.

11. The computer-implemented method of claim 1, wherein the method comprises presenting a plurality of selection queries to the plurality of users until a condition is satisfied.

12. The computer-implemented method of claim 11, wherein the condition comprises the lapsing of a period of time or the receiving a predetermined number of responses.

13. The computer-implemented method of claim 1, wherein the method comprises:

receiving, by the one or more computing devices, a veto decision from one of the plurality of users; and

removing, by the one or more computing devices, a candidate object from the plurality of candidate objects based on the veto decision.

14. The computer-implemented method of claim 1, the plurality of candidate objects comprise a plurality of restaurants.

15. A computing system, comprising:

a display device;

a processor; and

a memory, the memory storing computer-readable instructions that when executed by the processor cause the processor to perform operations, the operations comprising;

receiving a plurality of selection queries via a network interface, each of the plurality of selection queries requiring a user to select one or more of a plurality of keywords based on user preferences, the plurality of keywords being associated with one or more objects in a plurality of candidate objects, at least one keyword of the plurality of keywords being selected for inclusion in the plurality of selection queries based at least in part on a number of candidate objects associated with the at least one keyword;

presenting each of the plurality of selection queries in a user interface presented on a display device;

receiving a response to each of the plurality of selection queries;

providing the responses to each of the plurality of selection queries to a remote device over a network interface; and

receiving at least one group recommendation of an object via the network interface, the at least one group recommendation being determined based on ranking scores generated for the plurality of candidate objects based on responses to each of the plurality of selection from a plurality of users; and

presenting the at least one group recommendation in the user interface.

16. The computing device of claim 15, wherein each of the plurality of keywords area associated with a characteristic trait of at least one of the plurality of candidate object

17. The computing device of claim 15, wherein at least one of the plurality of selection queries requires the user to make a pairwise decision between two keywords.

18. The computing device of claim 15, wherein at least one of the plurality of selection queries requires the user to rank a plurality of keywords.

19. A computer-implemented method of providing a recommendation of a restaurant to a group, the method comprising:

identifying, by one or more computing devices, a plurality of candidate restaurants;

identifying, by the one or more computing devices, a plurality of keywords associated with characteristic traits of the plurality of candidate restaurants from at least one data store storing information associated with the plurality of candidate objects;

generating, by the one or more computing devices, a plurality of selection queries, each selection query presenting two or more keywords, each keyword being identified for inclusion in the selection query based on a number of candidate objects associated with the keyword in the at least one data store;

providing, by the one or more computing devices

providing, by the one or more computing devices, a plurality of selection queries to a plurality of users in the group, each of the plurality of selection queries requiring a user to select one or more of the plurality of keywords based on user preferences;

receiving, by the one or more computing devices, a response to each of the plurality of selection queries from the plurality of users;

generating, by the one or more computing devices, a ranking score for each of the plurality of candidate restaurants based on the responses to the plurality of selection queries; and

providing, by the one or more computing devices, at least one group recommendation of a restaurant determined based on the ranking scores for the plurality of candidate restaurants.

20. The computer-implemented method of claim 19, wherein the plurality of candidate restaurants are identified based on position data associated with one or more of the plurality of users.