1. A computer-implemented method for recommending one or more crowdsourcing platforms, from a plurality of crowdsourcing platforms, to a requester, the computer-implemented method comprising: receiving, by one or more processors, one or more values corresponding to one or more requirement parameters associated with one or more tasks from the requester, wherein a tolerance value is received for each of the one or more requirement parameters; determining, by the one or more processors, one or more values corresponding to one or more observable characteristics associated with each of the plurality of crowdsourcing platforms based on one or more responses received from the plurality of the crowdsourcing platforms for one or more sample tasks; retrieving, by the one or more processors, a plurality of statistical models from model data maintained for the plurality of crowdsourcing platforms, wherein the plurality of statistical models are associated with probabilities of the plurality of crowdsourcing platforms in executing the one or more tasks based on behavior of the plurality of crowdsourcing platforms from historic task statistics data; determining, by the one or more processors, a confidence score of each of the plurality of crowdsourcing platforms meeting the one or more requirement parameters associated with the one or more tasks, based on: a probability of each of the plurality of statistical models, the one or more requirement parameters, and the tolerance value of each of the one or more requirement parameters; and recommending, by the one or more processors, the one or more crowdsourcing platforms, based on the confidence score.
1. A computer-implemented method for recommending one or more crowdsourcing platforms, from a plurality of crowdsourcing platforms, to a requester, the computer-implemented method comprising: receiving, by one or more processors, one or more values corresponding to one or more requirement parameters associated with one or more tasks from the requester, wherein a tolerance value is received for each of the one or more requirement parameters; determining, by the one or more processors, one or more values corresponding to one or more observable characteristics associated with each of the plurality of crowdsourcing platforms based on one or more responses received from the plurality of the crowdsourcing platforms for one or more sample tasks; retrieving, by the one or more processors, a plurality of statistical models from model data maintained for the plurality of crowdsourcing platforms, wherein the plurality of statistical models are associated with probabilities of the plurality of crowdsourcing platforms in executing the one or more tasks based on behavior of the plurality of crowdsourcing platforms from historic task statistics data; determining, by the one or more processors, a confidence score of each of the plurality of crowdsourcing platforms meeting the one or more requirement parameters associated with the one or more tasks, based on: a probability of each of the plurality of statistical models, the one or more requirement parameters, and the tolerance value of each of the one or more requirement parameters; and recommending, by the one or more processors, the one or more crowdsourcing platforms, based on the confidence score. 8. The computer implemented method of claim 1 further comprising generating, by the one or more processors, a statistical model for each of the plurality of crowdsourcing platforms based on the one or more values corresponding to the one or more observable characteristics associated with respective crowdsourcing platform from the plurality of crowdsourcing platforms.