Abstract: At least one configured mobile device monitoring radius relative to respective purchase locations is established within a retail environment. Mobile device distances from purchase locations at times of purchases within the retail environment are monitored over time by a processor utilizing locationing technology. A repeating mobile device proximity pattern of at least two mobile device identifiers being located together and in proximity to the respective purchase locations at the times of the respective different purchases is detected across the several different purchases.

Abstract: At least one configured mobile device monitoring radius relative to respective purchase locations is established within a retail environment. Mobile device distances from purchase locations at times of purchases within the retail environment are monitored over time by a processor utilizing locationing technology. A repeating mobile device proximity pattern of at least two mobile device identifiers being located together and in proximity to the respective purchase locations at the times of the respective different purchases is detected across the several different purchases.

Abstract: Mobile device proximity to purchase locations at times of purchases within at least one retail environment is monitored over time by a processor utilizing locationing technology. Mobile device identifiers of mobile devices in proximity to the purchase locations within the at least one retail environment at the times of the purchases are captured. A repeating mobile device proximity pattern of at least two mobile device identifiers being repeatedly located together and in proximity to the respective purchase locations at the times of the respective purchases is detected across several different purchases. Mobile devices identified by the at least two mobile device identifiers detected within the repeating mobile device proximity pattern across the several different purchases are paired.

Abstract: A method, system and computer-usable medium are disclosed for enhancing a classification system to include an automatic classification validation system. The automatic classification validation system takes the classification results and automatically validates them for correctness. More specifically, the automatic classification validation system analyzes the data objects in the categories and, if any outliers are identified, then determines a context of the data object from a plurality of records contained within a certain category to determine the context. The classification validation system then uses the context of the data object to validate the classification.

Abstract: Mobile device proximity to purchase locations at times of purchases within at least one retail environment is monitored over time by a processor utilizing locationing technology. Mobile device identifiers of mobile devices in proximity to the purchase locations within the at least one retail environment at the times of the purchases are captured. A repeating mobile device proximity pattern of at least two mobile device identifiers being repeatedly located together and in proximity to the respective purchase locations at the times of the respective purchases is detected across several different purchases. Mobile devices identified by the at least two mobile device identifiers detected within the repeating mobile device proximity pattern across the several different purchases are paired.

Abstract: A method, system and computer-usable medium are disclosed for enhancing a classification system to include an automatic classification validation system. The automatic classification validation system takes the classification results and automatically validates them for correctness. More specifically, the automatic classification validation system analyzes the data objects in the categories and, if any outliers are identified, then determines a context of the data object from a plurality of records contained within a certain category to determine the context. The classification validation system then uses the context of the data object to validate the classification.