Abstract: A computer-implemented method for selecting a digital content, comprising: receiving a plurality of samples, each comprises a request having a plurality of values of a plurality of attributes, and associated with a success value for a Bernoulli distributed event having a campaign and a bid rate (BR) of the campaign; clustering the plurality of samples in a plurality of homogenous nodes according to respective plurality of values; identifying a group campaign with a highest valuation for each one of the plurality of nodes using triangular approximation of the Bernoulli distribution of events in the node; receiving a query from a device including a plurality of other values of the plurality of attributes; selecting one of the plurality of nodes; selecting a digital content of the group campaign with highest valuation identified for the selected node; and generating a response to the query including the selected content.

Abstract: A computer-implemented method for selecting a digital content, comprising: receiving a plurality of samples, each comprises a request having a plurality of values of a plurality of attributes, and associated with a success value for a Bernoulli distributed event having a campaign and a bid rate (BR) of the campaign; clustering the plurality of samples in a plurality of homogenous nodes according to respective plurality of values; identifying a group campaign with a highest valuation for each one of the plurality of nodes using triangular approximation of the Bernoulli distribution of events in the node; receiving a query from a device including a plurality of other values of the plurality of attributes; selecting one of the plurality of nodes; selecting a digital content of the group campaign with highest valuation identified for the selected node; and generating a response to the query including the selected content.