Abstract: Future media viewership is forecast based on time ordered analysis of historical viewership information from an individual or combination of a plurality of data sets. Forecast models having coefficients derived from comparisons of time series representations of data sets across a plurality of time periods and data sources join together disparate data sets. Individual data sets from disparate data sources may be compared to identify possible untrustworthy data or data that requires further investigation. Organizing viewership information in a time series allows for imputing missing data in a respective data set.

Abstract: In accordance with a method for determining a likelihood that two or more communication devices are associated with a common user, clickstream data from a plurality of clickstream events is received from each of a plurality of communication devices in response to a web page being loaded by each of the communication devices. The clickstream events received over a period of time are arranged into a datastream such that each of the datastreams contains clickstream events from only a single communication device. Based on the clickstream data in the clickstream events, potentially matching pairs of datastreams are identified that contain clickstream events from a common user using different communication devices. A statistical analysis is performed on the potentially matching pairs of datastreams in accordance with a statistical model in order to determine a likelihood that each of the potentially matching pairs of datastreams contain clickstream events from a common user.

Abstract: Future media viewership is forecast based on time ordered analysis of historical viewership information from an individual or combination of a plurality of data sets. Forecast models having coefficients derived from comparisons of time series representations of data sets across a plurality of time periods and data sources join together disparate data sets. Individual data sets from disparate data sources may be compared to identify possible untrustworthy data or data that requires further investigation. Organizing viewership information in a time series allows for imputing missing data in a respective data set.