Mutual commit people matching process
View Patent ↗A method and system for an automatic people matching with a mutual commit process is described. 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.
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 computer-generated inference of non-explicitly indicated preferences from 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 wherein one of the plurality of behaviors is generated through use of a mobile computing device;
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 computer-generated inference of non-explicitly indicated preferences from 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 computer-generated inference of non-explicitly indicated preferences from 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 computer-implemented function to determine the expected level of interest by a first party for a second party based, at least in part, on an inference of non-explicitly indicated preferences from a plurality of behaviors corresponding to a plurality of usage behavior categories;
a computer-implemented 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 computer-implemented 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 computer-implemented function to reveal to the parties the expression of mutual interest.
9. The system of claim 8 further comprising:
a computer-implemented function to deliver a recommendation to the first party of the second party.
10. The system of claim 9 further comprising:
a computer-implemented 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 computer-implemented function to determine the expected level interest by a first party for a second party based, at least in part, on an inference of non-explicitly indicated preferences from 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 computer-implemented function to determine the expected level interest by a first party for a second party based, at least in part, on an inference of non-explicitly indicated preferences from 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 computer-implemented 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 computer-implemented 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 computer-implemented 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 computer-implemented function to determine the parties' mutual commitment to reveal the mutual interest to each party.
15. A computer-based people matching system comprising:
a computer-implemented people recommendations function to generate people recommendations based, at least in part, on an inference of non-explicitly indicated preferences from a plurality of behaviors corresponding to a plurality of usage behavior categories;
a computer-implemented people matching function 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 computer-implemented function to reveal to the reciprocally recommended people the expression of mutual interest.
16. The system of claim 15 wherein a computer-implemented people recommendations function to generate people recommendations based, at least in part, on an inference of non-explicitly indicated preferences from a plurality of behaviors corresponding to a plurality of usage behavior categories comprises:
a computer-implemented 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 computer-implemented people matching function 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 comprises:
a computer-implemented function to evaluate physiological responses of the reciprocally recommended people.