Abstract: A processing system deployed in a telecommunication network may obtain data records including data associated with subscribers, cluster the subscribers into a plurality of clusters in accordance with the data, identify a first set of subscribers enrolled in automated clearing house (ACH) payment agreements, and identify a second set of subscribers not enrolled in ACH payment agreements, calculate distance measures for the second set of subscribers, where for each respective subscriber of the second set of subscribers, the distance measures include a respective distance measure of the respective subscriber to a feature centroid for a subset of the first set of subscribers in a same cluster as the respective subscriber, select a subset of the second set of subscribers based upon the plurality of distance measures for receiving an offer in an ACH payment agreement, and present communications to the subset of the second set of subscribers with the offer.

Abstract: A processing system deployed in a telecommunication network may obtain data records including data associated with subscribers, cluster the subscribers into a plurality of clusters in accordance with the data, identify a first set of subscribers enrolled in automated clearing house (ACH) payment agreements, and identify a second set of subscribers not enrolled in ACH payment agreements, calculate distance measures for the second set of subscribers, where for each respective subscriber of the second set of subscribers, the distance measures include a respective distance measure of the respective subscriber to a feature centroid for a subset of the first set of subscribers in a same cluster as the respective subscriber, select a subset of the second set of subscribers based upon the plurality of distance measures for receiving an offer in an ACH payment agreement, and present communications to the subset of the second set of subscribers with the offer.

Abstract: A method, computer-readable medium, and apparatus for providing customer care for customers are disclosed.

Abstract: A processing system deployed in a telecommunication network may obtain data records including data associated with subscribers, cluster the subscribers into a plurality of clusters in accordance with the data, identify a first set of subscribers enrolled in automated clearing house (ACH) payment agreements, and identify a second set of subscribers not enrolled in ACH payment agreements, calculate distance measures for the second set of subscribers, where for each respective subscriber of the second set of subscribers, the distance measures include a respective distance measure of the respective subscriber to a feature centroid for a subset of the first set of subscribers in a same cluster as the respective subscriber, select a subset of the second set of subscribers based upon the plurality of distance measures for receiving an offer in an ACH payment agreement, and present communications to the subset of the second set of subscribers with the offer.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, determining a first linear model and a first log-linear model according to first explanatory variables and a first plurality of occupancy estimates, determining a second linear model and a second log-linear model according to second explanatory variables and a second plurality of occupancy estimates, evaluating, according to a location of a building, the first linear model, the first log-linear model, the second linear model, and the second log-linear model according to first values of the first explanatory variables and second values of the second explanatory variables, and combining results from the evaluating to generate a mixed occupancy estimate. Other embodiments are disclosed.

Abstract: A method collects data and subjects it to statistical analysis to detect localized events, which assists in network provisioning. Illustratively, the data employed is hourly network traffic counts that are collected at cell sites. By taking advantage of the additive property of a Poisson process, the method integrates spatial neighbor information by aggregating temporal data in various areas, and iteratively estimating the event location and the radius of event impact by examining the posterior probability based on the aggregated data.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, determining a first linear model and a first log-linear model according to first explanatory variables and a first plurality of occupancy estimates, determining a second linear model and a second log-linear model according to second explanatory variables and a second plurality of occupancy estimates, evaluating, according to a location of a building, the first linear model, the first log-linear model, the second linear model, and the second log-linear model according to first values of the first explanatory variables and second values of the second explanatory variables, and combining results from the evaluating to generate a mixed occupancy estimate. Other embodiments are disclosed.

Abstract: A method that collects data and subjects it to statistical analysis to detect localized events, which assists in network provisioning. illustratively, the data employed is hourly network traffic count that is collected at cell sites. By taking the advantage of additive property of Poisson process, the method integrates spatial neighbor information by aggregating temporal data in various areas, and iteratively estimating the event location and the radius of event impact by examining the posterior probability base on the aggregated data.

Abstract: A method that collects data and subjects it to statistical analysis to detect localized events, which assists in network provisioning. Illustratively, the data employed is hourly network traffic count that is collected at cell sites. By taking the advantage of additive property of Poisson process, the method integrates spatial neighbor information by aggregating temporal data in various areas, and iteratively estimating the event location and the radius of event impact by examining the posterior probability base on the aggregated data.

Abstract: A method that collects data and subjects it to statistical analysis to detect localized events, which assists in network provisioning. Illustratively, the data employed is hourly network traffic count that is collected at cell sites. By taking the advantage of additive property of Poisson process, the method integrates spatial neighbor information by aggregating temporal data in various areas, and iteratively estimating the event location and the radius of event impact by examining the posterior probability base on the aggregated data.