FIELD: physics, computation hardware.
SUBSTANCE: invention relates to detection of patterns in pay card transaction data to define the seller affiliation group in said data. Proposed method comprises memorising of transaction data in data base, transaction data sampling by first computer connected with data base, use of at least one algorithm of forecasting and selected transaction data for forecasting multiple group seller affiliation in group of sellers. Note here that algorithm is executed by first computer. It comprises generation of metadata describing every forecast outputted by at least one said algorithm, input of multiple forecast group affiliations for seller and metadata describing every forecast into data analysis program to be executed at second computer. Second computer is used to assign confidence factor to every forecast group affiliation with the help of data analysis program. Said group affiliation is based on at least partially forecast group affiliation and metadata. Note here that confidence factor represents a probability of actual association of the seller with appropriate forecast group affiliation. Second computer is used to forecast the group affiliation with the highest confidence factor as the final forecast of seller affiliation.
EFFECT: higher accuracy of forecasting of the seller affiliation with different groups of sellers.
20 cl, 10 dwg
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Authors
Dates
2014-04-10—Published
2008-12-04—Filed