Abstract: A method and apparatus for determining geographic clusters of geographical content may include computation of a first evaluation metric. The first evaluation metric may be descriptive of a distribution of geo-location points within a cluster of a plurality of geographic clusters. A second evaluation metric may also be computed that is descriptive of coherence of the plurality of geographic clusters. Geo-location points of the geographical content may be clustered based, at least in part on the first and second evaluation metrics.

Abstract: The present disclosure relates to a computer system configured establish and utilize a database for online ad realization prediction in an ad display platform associated with N parties, wherein N is a positive integral greater than 1. The computer system is configured obtain a party hierarchy for each of the N parties including a plurality of features of the party; select a target ad display event including N features, each of the N features corresponding to a node in a party hierarchy; obtain a prior probability reflecting an unconditional probability of ad realization occurrence at the target ad display event among all possible ad display events; for each of the N features: determine a marginal prior probability by decomposing components associated with the other N?1 features from the prior probability; determine a marginal posterior probability based on the marginal prior probability; and save the marginal posterior probability in the corresponding node of the party hierarchy.

Abstract: A method and apparatus for determining geographic clusters of geographical content may include computation of a first evaluation metric. The first evaluation metric may be descriptive of a distribution of geo-location points within a cluster of a plurality of geographic clusters. A second evaluation metric may also be computed that is descriptive of coherence of the plurality of geographic clusters. Geo-location points of the geographical content may be clustered based, at least in part on the first and second evaluation metrics.

Abstract: The present disclosure relates to a computer system configured establish and utilize a database for online ad realization prediction in an ad display platform associated with N parties, wherein N is a positive integral greater than 1. The computer system is configured obtain a party hierarchy for each of the N parties including a plurality of features of the party; select a target ad display event including N features, each of the N features corresponding to a node in a party hierarchy; obtain a prior probability reflecting an unconditional probability of ad realization occurrence at the target ad display event among all possible ad display events; for each of the N features: determine a marginal prior probability by decomposing components associated with the other N?1 features from the prior probability; determine a marginal posterior probability based on the marginal prior probability; and save the marginal posterior probability in the corresponding node of the party hierarchy.