Method and system for creating events and matching users via blended profiles

• US 8,793,314 B2
• Filed: 05/21/2012
• Issued: 07/29/2014
• Est. Priority Date: 05/20/2011
• Status: Expired due to Fees

• Current Assignee: Blendabout, Inc.
• Original Assignee: Blendabout, Inc.
• Inventors: Spivak, Katharine D., Winters, Jon H.
• Primary Examiner(s): Wang, Liangche A
• Assistant Examiner(s): AGUIAR, JOHNNY B
• Application Number:
  US13/476,993
• Publication Number:
  US 20120296973A1
• Time in Patent Office: 799 Days
• Field of Search: 709/204, 709/203, 709/217, 707/737, 707/758, 705/319, 715/751
• US Class Current: 709/204
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task
• CPC Class Codes: G06Q 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

Certain embodiments teach a method and system for pairing users, whom do not know each other for an event, on a social networking platform. The social dining system matches people with common interests and organizes an offline event, such as a meal at a restaurant, based on user profiles, availability, and other attributes. For example, the social dining system can schedule a group meal for a user, and five to seven other people that share an interest with the user. In cases where a user prefers to be attend events with at least one known user, a single profile for the user and the known user is created as a mutual or a blended profile. The system then creates an event by matching the mutual profile with other members using a blending algorithm.

Claims

1. A method of scheduling a social dining event by matching a blended profile with a set of entities:

receiving, by a social dining system, profile parameters which enable a plurality of blended profiles to be created, wherein each blended profile is an abstract data structure including information relating to at least two or more members, wherein the at least two or more members are acquainted with each other, wherein the profile parameters include attributes of each member of the at least two or more members, and wherein the attributes of each member of the at least two or more members in each blended profile are aggregated as a particular single merged entity for processing based on mutually shared attributes;

receiving, by the social dining system, event parameters which enable scheduling of a plurality of social dining events, wherein the scheduling of each social dining event includes arranging an appointment between the particular single merged entity and a particular set of entities at a restaurant, and wherein the event parameters include availability attributes of each member of the particular single merged entity and each member of the particular set of entities;

identifying, by the social dining system, a first blended profile from the plurality of blended profiles, the first blended profile being a single merged entity having a set of mutual attributes, the identifying including;

identifying a first set of attributes for a first member of the first blended profile and a second set of attributes for a second member of the first blended profile, wherein the first member and the second member are acquainted with each other; and

identifying a first restaurant wish list for the first member and a second restaurant wish list for the second member, the first and second restaurant wish lists each including a plurality of ranked restaurants, wherein the plurality of ranked restaurants is listed in an order based on a ranking by a respective member of the first blended profile and based on a monitoring of user activity of the respective member on the social dining system, the user activity indicative of an interest in a particular restaurant; and

identifying a first user wish list for the first member and identifying a second user wish list for the second member, the first and second user wish lists each including a set of members that is received, by the social dining system, as an add request from the respective member browsing a directory of members of the social dining system;

determining, by the social dining system, the set of mutual attributes, the set of mutual attributes including common attributes between the first and second sets of attributes, common restaurants between the first and second restaurant wish lists, and common users between the first and second user wish lists;

applying, by the social dining system, a weight to each mutual attribute of the set of mutual attributes;

determining, by the social dining system, a first set of entities matching with the single merged entity by applying a blending algorithm, said determining, based, at least in part, on the set of mutual attributes, wherein the first set of entities is either (a) a member that is not the first or second member, or (b) a particular blended profile not including the first blended profile; and

arranging, by the social dining system, a first social dining event between the single merged entity and the first set of entities matched by the blending algorithm, wherein the arranging includes communicating with a restaurant system to make reservation at the restaurant for the first social dining event.

2. The method of claim 1, wherein the common attributes between the first and second sets of attributes include any one of:

a preferred geographical location, a willingness to travel, a favorite cuisine, an activity, or an interest.

3. The method of claim 1, wherein the blending algorithm utilizes a quality-thresholding clustering.

4. The method of claim 1, wherein determining, by the social dining system, the first set of entities comprises:

matching the first blended profile with a second blended profile; and

matching the first blended profile with a third blended profile.

5. A system for creating a social event by matching a mutual profile with a set of entities, comprising:

a processor;

a mutual profile module coupled to the processor to;

receive profile parameters which enable a plurality of mutual profiles to be created, wherein each mutual profile is an abstract data structure including information relating to at least two or more members, wherein the at least two or more members are acquainted with each other, wherein the profile parameters include attributes of each member of the at least two or more members, and wherein the attributes of the at least two or more members in each mutual profile are aggregated as a particular single merged entity for processing based on mutually shared attributes; and

an event scheduling module coupled to the processor to;

receive event parameters which enable scheduling of a social event, wherein the scheduling of the social event includes arranging a meeting between the mutual profile and the set of entities at a business venue, and wherein the event parameters includes availability attributes of each member of the mutual profile and each entity of the set of entities;

identify a first mutual profile from the plurality of mutual profiles, the first mutual profile being a single merged entity including a first member and a second member, the first and second members having a set of mutual attributes, wherein to identify further includes to;

identify a first set of attributes for the first member of the single merged entity and a second set of attributes for the second member of the single merged entity; and

identify a first venue wish list for the first member and a second venue wish list for the second member, the first and second venue wish lists each including a plurality of ranked venues, wherein the plurality of ranked venues is listed in an order based on a ranking by a respective member of the first and second members and based on a monitoring of user activity of the respective member using the system, the user activity indicative of an interest in a particular venue;

determine the set of mutual attributes, the set of mutual attributes including common attributes between the first set of attributes and the second set of attributes and common venues between the first venue wish list and the second venue wish list;

apply a weight to each mutual attribute of the set of mutual attributes;

determine, by use of a blending algorithm, the set of entities matching with the single merged entity based, at least in part, on the set of mutual attributes, wherein the set of entities is either (a) a particular member that is not the first or second member, or (b) a particular mutual profile not including the first mutual profile; and

arrange a first social event between the single merged entity and the set of entities matched by the blending algorithm, wherein to arrange includes to;

transmit an event invitation to each member of (a) the single merged entity and (b) the set of entities, the event invitation configured to request a confirmation from each member for attending the first social event; and

responsive to the confirmation, communicate with a venue system to make reservation for a set of members at the venue, the set of members based on a number of confirmations received from the single merged entity and the set of entities.

6. The system of claim 5, wherein the common attributes between the first and second sets of attributes include any one of:

a preferred geographical location, a willingness to travel, a favorite cuisine, an activity, or an interest.

7. The system of claim 5, wherein the system further comprises a friends module coupled to the processor to identify a first user wish list for the first member and to identify a second user wish list for the second member;

and wherein the set of mutual attributes further includes common users between the first user wish list and the second user wish list.

8. The system of claim 5, wherein to determine, by use of the blending algorithm, includes:

matching the first mutual profile with a second mutual profile and matching the first mutual profile with a third mutual profile.

9. The method of claim 5, wherein the blending algorithm utilizes a quality-thresholding clustering.

10. A method comprising:

receiving profile parameters which enable a blended profile to be created, wherein the blended profile is a single merged entity including information on a first member and a second member, wherein the first and second members are acquainted with each other, wherein the profile parameters include attributes of each member of the first and second members, and wherein the attributes of the first member are aggregated with the attributes of the second member as the single merged entity for processing based on mutually shared attributes;

receiving event parameters which enable scheduling of a social event, wherein the scheduling of the social event includes arranging a gathering between the blended profile and at least two other blended profiles at a restaurant, and wherein the event parameters include availability attributes of each member of the blended profile and each member of the at least two other blended profiles;

identifying the blended profile, wherein the identifying includes;

identifying a first set of attributes for the first member and a second set of attributes for the second member;

identifying a first restaurant wish list for the first member and a second restaurant wish list for the second member, the first and second restaurant wish lists each including a plurality of ranked restaurants, wherein the plurality of ranked restaurants is listed in an order based on a ranking by a respective member of the blended profile and based on a monitoring of user activity of the respective member on the social dining system, the user activity indicative of an interest in a particular restaurant; and

identifying a first user wish list for the first member and identifying a second user wish list for the second member, the first and second user wish lists each including a set of members that is received, by the social dining system, as an add request from the respective member browsing a directory of members of the social dining system;

determining a set of mutual attributes, the set of mutual attributes including common attributes between the first and second sets of attributes, common restaurants between the first and second restaurant wish lists, and common users between the first and second user wish lists;

applying a weight to each mutual attribute of the set of mutual attributes;

determining the at least two other blended profiles matching with the blended profile by applying a blending algorithm, said determining based, at least in part, on the set of mutual attributes, wherein the at least two other blended profiles do not include the first member and do not include the second member; and

arranging a first social event between the blended profile and the at least two other blended profiles matched by the blending algorithm.

11. The method of claim 10, wherein the common attributes between the first and second sets of attributes include any one of:

a preferred geographical location, a willingness to travel, a favorite cuisine, an activity, or an interest.

12. The method of claim 10, wherein the blending algorithm utilizes a quality-thresholding clustering.

13. The method of claim 10, wherein determining the at least two other blended profiles matching with the blended profile by applying blending algorithm further includes:

matching the first blended profile with a second blended profile and matching the first blended profile with a third blended profile.