Abstract: A data source is monitored. During the monitoring, an arrival at the data source of each of one or more sets of one or more features is detected. In response to detecting the arrival at the data source of at least a first set of one or more features of the one or more sets of one or more features, data is extracted from the first set of one or more features, data for at least a second set of one or more features of the one or more sets of one or more features is estimated, wherein the second set of one or more features has not yet arrived at the data source, and, based on the extracted data and the estimated data, a data quality metric is predicted.

Abstract: A system and method may be used to automatically select one of a plurality of advertisements to display on a computing device, for example, via online delivery of a gallery last-page advertisement or the like. A prior probability distribution may be obtained, and may be indicative of the relative likelihood of activation of the plurality of advertisements by a user. Bayesian statistical inference may be applied to the prior probability distribution to generate a posterior probability distribution that indicates relative likelihood of activation of the plurality of advertisements by the user, for example, with greater accuracy than the prior probability distribution. The posterior probability distribution may be used to select a first advertisement of the plurality of advertisements. A signal may be transmitted to cause the first advertisement to be displayed to the user.