Automated entity identification for efficient profiling in an event probability prediction system

Anthony Vaiciulis, Larry Peranich, Uwe Mayer, Scott Zoldi and Shane De Zilwa

Abstract: A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.


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mayer@math.utah.edu
Tue Feb 28 19:07:45 PST 2012