Patent ID: 8429182

Claim:
A computer implemented method of populating a task directed community, the computer implemented method comprising: a processor identifying non-linear attributes of each member of a first cohort, wherein the first cohort is a task directed community that has a first agenda, and wherein each of the non-linear attributes is individually unrelated to the first agenda; the processor identifying common non-linear attributes that are shared by multiple members of the first cohort; the processor defining a paradigmatic member of the first cohort based on the common non-linear attributes of the members of the first cohort and at least one constraint on the first cohort; the processor mapping the paradigmatic member of the first cohort to the common non-linear attributes of the members of the first cohort and said at least one constraint on the first cohort for storage of same; the processor identifying a second agenda of a second cohort; the processor comparing the second agenda to the first agenda; the processor executing a Bayesian analysis to determine enrollment candidates to the second cohort, wherein the Bayesian analysis is performed by executing the formula: P ⁡ ( A | B ) = P ⁡ ( B | A ) * P ⁡ ( A ) P ⁡ ( B ) where: P(A|B) is a probability that a candidate person will meet cohort requirements of the second cohort (A) given (|) that the candidate person has same attributes as the paradigmatic member (B) of the first cohort, where (|) is a conditional operator representing A given a condition B; P(B|A) is a probability that a known member of the first cohort has same attributes as the paradigmatic member (B) of the first cohort; P(A) is a probability that the candidate person will meet the cohort requirements of the second cohort regardless of any other information; and P(B) is a probability that the candidate person will have the same attributes as the paradigmatic member regardless of any other information; the processor, in response to the first agenda matching the second agenda within predefined bounds, locating enrollment candidates for the second cohort, wherein the enrollment candidates hold the common non-linear attributes that are mapped to the paradigmatic member of the first cohort; and the processor, subject to at least one constraint on the second cohort, providing information describing the located enrollment candidates to the second cohort.