1. A method comprising:
receiving, by a computer, in response to a computer automated survey, responses from an individual to multiple survey questions related to attitudinal factors, the individual being enrolled in a consumer directed health plan or high deductible health plan;
receiving factual profile information about the individual, the factual profile information including one or more of income, credit score, credit balance, gender, marital status, number of dependents, arrest record, and driving record;
predicting, by the computer, a personality trait for the individual based on responses received from the individual in response to the computer automated survey and the factual profile information about the individual, the personality trait being associated at least in part with at least one of spending attitudes of the individual and attitudes of the individual toward medical treatment;
receiving information related to the usage of the consumer directed health plan or high deductible health plan by the individual;
receiving information related to the income of the individual; and
providing, based on the predicted personality trait for the individual, the information related to the usage, and the information related to the income of the individual, information about use of the consumer directed health plan or high deductible health plan to the individual, the information being different for different individuals having different predicted personality traits and different income levels:
wherein providing the information comprises:
for individuals having a particular personality trait, providing information related to reducing costs to the individual for medical services to individuals having an income below a threshold and providing information related to preventative healthcare to individuals having an income above the threshold.
2. The method of claim 1, wherein the method further comprises:
determining, based on the predicted personality trait for the individual, the individual’s suitability for a consumer directed health plan or high deductible health plan; and
providing the information comprises:
providing, to individuals determined to be suitable for a consumer directed health plan or high deductible health plan, one or more of information related to preventative healthcare and information related to reducing costs to the individual for medical services; and
providing, to individuals determined to be unsuitable for a consumer directed health plan or high deductible health plan, one or more of information about changing the individual’s type of health plan and information about appropriate use of the consumer directed health plan or high deductible health plan.
3. The method of claim 1, wherein the information about use of the consumer directed health plan or high deductible health plan comprises information related to locating a health care, provider.
4. The method of claim 1, wherein the predicted personality trait is based on a measure of financial astuteness of the individual.
5. The method of claim 1, wherein predicting the personality trait for the individual comprises predicting the personality trait for the individual based on at least one of past interaction information, demographic data, and credit bureau data.
6. The method of claim 1, wherein computer automated survey comprises 30 questions or fewer.
7. A method comprising:
receiving, by a computer, in response to a computer automated survey, responses from an individual to multiple survey questions related to attitudinal factors, the individual being enrolled in a consumer directed health plan or high deductible health plan;
receiving factual profile information about the individual, the factual profile information including one or more of income, credit score, credit balance gender, marital status, number of dependents, arrest record, and driving record;
predicting, by the computer, a personality trait for the individual based on responses received from the individual in response to the computer automated survey and the factual profile information about the individual, the personality trait being associated at least in part with at least one of spending attitudes of the individual and attitudes of the individual toward medical treatment;
receiving information related to the usage of the consumer directed health plan or high deductible health plan by the individual;
receiving information related to the income of the individual; and
providing, based on the predicted personality trait for the individual, the information related to the usage, and the information related to the income of the individual information about use of the consumer directed health plan or high deductible health plan to the individual, the information being different for different individuals having different predicted personality traits and different income levels;
determining, based on the predicted personality trait for the individual, the individual’s suitability for a consumer directed health plan or high deductible health plan; and
wherein providing the information comprises:
providing, to individuals determined to be suitable for a consumer directed health plan or high deductible health plan, one or more of information related to preventative healthcare and information related to reducing costs to the individual for medical services; and
providing, to individuals determined to be unsuitable for a consumer directed health plan or high deductible health plan, one or more of information about changing the individual’s type of health plan and information about appropriate use of the consumer directed health plan or high deductible health plan.
8. The method of claim 7, wherein providing the information comprises:
for individuals having a particular personality trait, providing information related to reducing costs to the individual for medical services to individuals having an income below a threshold and providing information related to preventative healthcare to individuals having an income above the threshold.
9. The method of claim 7, wherein the information about use of the consumer directed health plan or high deductible health plan comprises information related to locating a health care provider.
10. The method of claim 7, wherein the predicted personality trait is based on a measure of financial astuteness of the individual.
11. The method of claim 7, wherein predicting the personality trait for the individual comprises predicting the personality trait for the individual based on at least one of past interaction information, demographic data, and credit bureau data.
12. The method of claim 7, wherein computer automated survey comprises 30 questions or fewer.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method for selecting one or more matching end users for an end user to be matched on an online social platform where end users participate in different forms of electronic communications with varying levels of engagement with other end users, comprising:
determining a first set of end users who have participated in a first form of electronic communication with the end user to be matched;
determining a second set of end users who have participated in the first form of electronic communication with one or more end users in the first set of end users, the second set of end users being end users who are similar to the end user being matched;
determining a third set of end users who have participated in the first form of electronic communication with one or more end users in the second set of end users;
computing a score value for an end user in the third set of end users based on a sum of products, each product is a product of a coefficient and a variable;
wherein the coefficients correspond to effects of the variables on the score value;
wherein the variables used in computing the score value for a particular end user comprises:
a triangulation variable based on the number of end users in the second set of end users with whom the particular end user has participated in the first form of electronic communication; and
one or more search criteria variables based on whether the particular end user has user profile attributes which meets the search criteria of the end user to be matched; and
selecting the one or more matching end users based on the score values computed for the end users in the third set of end users.
2. The method according to claim 1, wherein the coefficients used if the end user to be matched is female differ from the coefficients used for each variable if the end user to be matched is male.
3. The method according to claim 1, wherein the one or more search criteria variables used if an end user to be matched is female, are different from the one or more search criteria variables used if the end user to be matched is male.
4. The method according to claim 1, wherein:
the score value represents a probability that the particular end user will engage in one form of electronic communication with the end user to be matched; and
the sum of products are provided based on a logistic regression model for computing the probability.
5. The method according to claim 1, further comprising:
if any of the first set of end users, the second set of end users, and the third set of end user is an empty set, repeating the determining steps based on participation in a second form of electronic communication, wherein the second form of electronic communication indicates a level of engagement that is lower than the level of engagement indicated by the second form of electronic communication.
6. The method according to claim 5, further comprising:
repeating the computing step using a different sum of products having different coefficients and different variables.
7. The method according to claim 1, wherein the one or more the search criteria variables include:
a distance variable measuring a distance between the location of the particular end user and the location of the end user to be matched;
wherein coefficient corresponding to the distance variable is provided such that the distance variable contributes negatively to the score value.
8. The method according to claim 1, wherein at least one of the one or more the search criteria variables takes into account a positive ratings variable as a trade-off based on whether the particular end user is well received by other end users on the online social platform when determining whether the particular end user has user profile attributes which meets the search criteria of the end user to be matched.
9. The method of claim 1, wherein the third set of end users are selected from a pool of end users who meet one or more of the following requirements:
the end user has not already been rated by the end user being matched;
the end user has not already been selected as a matching end user for the end user being matched in the past; and
the end user has not already participated in a form of electronic communication with the end user being matched in the past.
10. The method of claim 1, wherein at least one of the one or more search criteria variables is relaxed within a buffer when determining whether the particular end user has user profile attributes which meets the search criteria of the end user to be matched.
11. The method of claim 10, wherein the buffer is provided if the particular end user or the end user to be matched meets one or more conditions.
12. The method of claim 10, wherein the buffer is not provided if the particular end user or the end user to be matched meets one or more conditions.
13. One or more non-transitory tangible media that includes code for execution and when executed by a processor is operable to perform operations for selecting one or more matching end users for an end user to be matched on an online social platform where end users participate in different forms of electronic communications with varying levels of engagement with other end users, the operations comprising:
determining a first set of end users who have participated in a first form of electronic communication with the end user to be matched;
determining a second set of end users who have participated in the first form of electronic communication with one or more end users in the first set of end users, the second set of end users being end users who are similar to the end user being matched;
determining a third set of end users who have participated in the first form of electronic communication with one or more end users in the second set of end users;
computing a score value for an end user in the third set of end users based on a sum of products, each product is a product of a coefficient and a variable;
wherein the coefficients correspond to effects of the variables on the score value;
wherein the variables used in computing the score value for a particular end user comprises:
a triangulation variable based on the number of end users in the second set of end users with whom the particular end user has participated in the first form of electronic communication; and
one or more search criteria variables based on whether the particular end user has user profile attributes which meets the search criteria of the end user to be matched; and
selecting the one or more matching end users based on the score values computed for the end users in the third set of end users.
14. The media according to claim 13, wherein the coefficients used if the end user to be matched is female differ from the coefficients used for each variable if the end user to be matched is male.
15. The media according to claim 13, wherein the one or more search criteria variables used if an end user to be matched is female, are different from the one or more search criteria variables used if the end user to be matched is male.
16. The media according to claim 13, wherein:
the score value represents a probability that the particular end user will engage in one form of electronic communication with the end user to be matched; and
the sum of products are provided based on a logistic regression model for computing the probability.
17. A server for selecting one or more matching end users an end user to be matched on an online social platform where end users participate in different forms of electronic communications with varying levels of engagement with other end users, the server comprising:
a memory for storing a log of the different forms of electronic communications occurring through the online social platform; and
a processor for:
determining a first set of end users who have participated in a first form of electronic communication with the end user to be matched;
determining a second set of end users who have participated in the first form of electronic communication with one or more end users in the first set of end users, the second set of end users being end users who are similar to the end user being matched;
determining a third set of end users who have participated in the first form of electronic communication with one or more end users in the second set of end users;
computing a score value for an end user in the third set of end users based on a sum of products, each product is a product of a coefficient and a variable;
wherein the coefficients correspond to effects of the variables on the score value;
wherein the variables used in computing the score value for a particular end user comprises:
a triangulation variable based on the number of end users in the second set of end users with whom the particular end user has participated in the first form of electronic communication; and
one or more search criteria variables based on whether the particular end user has user profile attributes which meets the search criteria of the end user to be matched; and
selecting the one or more matching end users based on the score values computed for the end users in the third set of end users.
18. The system according to claim 17, wherein the coefficients used if the end user to be matched is female differ from the coefficients used for each variable if the end user to be matched is male.
19. The system according to claim 17, wherein the one or more search criteria variables used if an end user to be matched is female, are different from the one or more search criteria variables used if the end user to be matched is male.
20. The system according to claim 17, wherein:
the score value represents a probability that the particular end user will engage in one form of electronic communication with the end user to be matched; and
the sum of products are provided based on a logistic regression model for computing the probability.