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 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 and system for mining a database for product migration analysis includes querying product usage data for a legacy product and a new product from the database as time series data. The product usage data is representative for a large number of consumers of the legacy and new products. A mathematical model may be used to determine a relationship between the two time series data. Product migration values and other features related to product migration, such as a transition period of product usage, may be estimated, determined or predicted.

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 and system for mining a database for product migration analysis includes querying product usage data for a legacy product and a new product from the database as time series data. The product usage data is representative for a large number of consumers of the legacy and new products. A mathematical model may be used to determine a relationship between the two time series data. Product migration values and other features related to product migration, such as a transition period of product usage, may be estimated, determined or predicted.