Mutual Commit People Matching Process

• US 20080052288A1
• Filed: 08/26/2007
• Published: 02/28/2008
• Est. Priority Date: 08/28/2006
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Manyworlds Incorporated
• Inventors: Flinn, Steven Dennis, Moneypenny, Naomi Felina
• Granted Patent: US 7,739,231 B2
• Time in Patent Office: Days
• US Class Current: 707/6
• CPC Class Codes: G06F 15/17306 Intercommunication techniques
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/90 Details of database functions independent of the retrieved data types
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 51/04 Real-time or near real-time messaging, e.g. instant messaging [IM]
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/14 Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]

Abstract

A method and system for an automatic people matching with a mutual commit process is disclosed. The process includes a recommender system that generates people recommendations based, at least in part, on inferences of preferences derived from system usage behaviors. The process also includes variations of a mutual commitment process that may only reveal a first party'"'"'s interest in making their expression of interest with a second party if a reciprocal interest in revealing expression of interest is indicated. The process enhances social networking by reducing potential embarrassment and fear of rejection.

Claims

1. A computer-based people matching method comprising:

determining the expected level of interest by a first party for a second party based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories;

determining the expected level of interest by the second party for the first party based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories;

determining if the level of mutual interest expressed by the parties is sufficient to reveal the expression of mutual interest to the parties; and

revealing to the parties the expression of mutual interest.

2. The method of claim 1 further comprising:

delivering a recommendation to the first party of the second party.

3. The method of claim 2 further comprising:

delivering an explanation to the first party of why the second party was recommended to the first party comprising, at least in part, of behavioral-based information.

4. The method of claim 1 wherein determining the expected level interest by a first party for a second party based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories comprises:

evaluating a behavior corresponding to a physiological responses usage behavior category.

5. The method of claim 1 wherein determining the expected level interest by a first party for a second party based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories comprises:

evaluating a behavior corresponding to an environmental conditions and location usage behavior category.

6. The method of claim 1 wherein determining if the level of mutual interest expressed by the parties is sufficient to reveal the expression of mutual interest to the parties comprises:

randomizing recommendations wherein a recommendation of a second party to a first party does not guarantee a recommendation of the first party to the second party.

7. The method of claim 1 wherein determining if the level of mutual interest expressed by the parties is sufficient to reveal the expression of mutual interest to the parties comprises:

determining the parties'"'"' mutual commitment in revealing the mutual interest to each party.

8. A computer-based people matching system comprising:

a function to determine the expected level of interest by a first party for a second party based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories;

a function to determine the expected level of interest by the second party for the first party based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories;

a function to determine if the level of mutual interest expressed by the parties is sufficient to reveal the expression of mutual interest to the parties; and

a function to reveal to the parties the expression of mutual interest.

9. The system of claim 8 further comprising:

a function to deliver a recommendation to the first party of the second party.

10. The system of claim 9 further comprising:

a function to deliver an explanation to the first party of why the second party was recommended to the first party comprising, at least in part, of behavioral-based information.

11. The system of claim 8 wherein a function to determine the expected level interest by a first party for a second party based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories comprises:

a behavior corresponding to a physiological responses usage behavior category.

12. The system of claim 8 wherein a function to determine the expected level interest by a first party for a second party based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories comprises:

a behavior corresponding to an environmental conditions and location usage behavior category.

13. The system of claim 8 wherein a function to determine if the level of mutual interest expressed by the parties is sufficient to reveal the expression of mutual interest to the parties comprises:

a function to randomize recommendations wherein a recommendation of a second party to a first party does not guarantee a recommendation of the first party to the second party.

14. The system of claim 8 wherein a function to determine if the level of mutual interest expressed by the parties is sufficient to reveal the expression of mutual interest to the parties comprises:

a function to determine the parties'"'"' mutual commitment to reveal the mutual interest to each party.

15. A computer-based people matching system comprising:

a people recommendations function comprising means to generate people recommendations based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories;

a people matching function comprising means to determine by evaluating usage behaviors if the level of mutual interest expressed by reciprocally recommended people recommended by the people recommendations function is sufficient to reveal the expression interest of mutual interest to the parties; and

a function to reveal to the reciprocally recommended people the expression of mutual interest.

16. The system of claim 15 wherein a people recommendations function comprising means to generate people recommendations based, at least in part, on a plurality of behaviors corresponding to a plurality of usage behavior categories comprises:

a function to generate an explanation of why a first person was recommended to a second person, comprising, at least in part, behavioral-based information.

17. The system of claim 15 wherein a people matching function comprising means to determine by evaluating mutual usage behaviors if the level of mutual interest expressed by reciprocally recommended people recommended by the people recommendations function is sufficient to reveal the expression of mutual interest to the parties comprises:

a function to evaluate physiological responses of the reciprocally recommended people.