SYSTEM AND METHOD FOR REPRESENTING INCONSISTENTLY FORMATTED DATA SETS
First Claim
1. A method for generating a suggested insurance decision, the method comprising:
- storing a first data set in a computer, said first data set containing data related to public driving record information;
storing a second set of data in the computer, said second data set containing data gathered telematically with respect to a first plurality of drivers, said second data set having a different format from said first data set;
processing the first data set with the computer to generate a first Bayesian Belief Network that represents the first data set;
processing the second data set with the computer to generate a second Bayesian Belief Network that represents the second data set;
combining the first and second Bayesian Belief Networks to form a combined Bayesian Belief Network that represents a virtual data set, said virtual data set encompassing at least a portion of each of said first and second data sets;
receiving input with respect to a proposed or current insured; and
generating a signal indicative of a suggested insurance decision with respect to the proposed or current insured, based at least in part on (a) the received input with respect to the proposed or current insured and (b) the combined Bayesian Belief Network.
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Abstract
Two or more data sets, arranged in mutually inconsistent formats, are stored in a computer. Software is applied to each data set to discover and generate a topology for a respective Bayesian Belief Network for each of the data sets. The resulting individual constituent Bayesian Belief Networks are combined to produce a combined Bayesian Belief Network. The combined Bayesian Belief Network represents a virtual data set that does not exist but which stands in for a combination of the original data sets. The combined Bayesian Belief Network is a convenient representation that may be analyzed to investigate causality relationships among all of the variables in the constituent data sets.
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Citations
21 Claims
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1. A method for generating a suggested insurance decision, the method comprising:
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storing a first data set in a computer, said first data set containing data related to public driving record information; storing a second set of data in the computer, said second data set containing data gathered telematically with respect to a first plurality of drivers, said second data set having a different format from said first data set; processing the first data set with the computer to generate a first Bayesian Belief Network that represents the first data set; processing the second data set with the computer to generate a second Bayesian Belief Network that represents the second data set; combining the first and second Bayesian Belief Networks to form a combined Bayesian Belief Network that represents a virtual data set, said virtual data set encompassing at least a portion of each of said first and second data sets; receiving input with respect to a proposed or current insured; and generating a signal indicative of a suggested insurance decision with respect to the proposed or current insured, based at least in part on (a) the received input with respect to the proposed or current insured and (b) the combined Bayesian Belief Network. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A method comprising:
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deriving a first Bayesian Belief Network from a first data set; deriving a second Bayesian Belief Network from a second data set; providing at least one link between the first and second Bayesian Belief Networks to generate a composite Bayesian Belief Network, said composite Bayesian Belief Network representing a virtual data set that encompasses at least a portion of each of the first and second data sets; and storing the composite Bayesian Belief Network in a computer. - View Dependent Claims (15, 16, 17)
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18. A computer system for generating a suggested insurance decision, the computer system comprising:
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a processor; and a memory in communication with the processor and storing program instructions, the processor operative with the program instructions to; store a first data set in a computer, said first data set containing data related to public driving record information; store a second set of data in the computer, said second data set containing data gathered telematically with respect to a first plurality of drivers, said second data set having a different format from said first data set; process the first data set with the computer to generate a first Bayesian Belief Network that represents the first data set; process the second data set with the computer to generate a second Bayesian Belief Network that represents the second data set; combine the first and second Bayesian Belief Networks to form a combined Bayesian Belief Network that represents a virtual data set, said virtual data set encompassing at least a portion of each of said first and second data sets; receive input with respect to a proposed or current insured; and generate a signal indicative of a suggested insurance decision with respect to the proposed or current insured, based at least in part on (a) the received input with respect to the proposed or current insured and (b) the combined Bayesian Belief Network.
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19. A method for generating a suggested insurance decision, the method comprising:
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storing a first data set in a computer, said first data set containing data related to public driving record information; storing a second set of data in the computer, said second data set containing data gathered telematically with respect to a first plurality of drivers, said second data set having a different format from said first data set; processing the first data set with the computer to generate a first graphical representation that indicates statistical independence relationships among variables in the first data set; processing the second data set with the computer to generate a second graphical representation that indicates statistical independence relationships among variables in the second data set; combining the first and second graphical representations to form a third graphical representation that combines at least a portion of the first graphical representation with at least a portion of the second graphical representation; receiving input with respect to a proposed or current insured; and generating a signal indicative of a suggested insurance decision with respect to the proposed or current insured, based at least in part on (a) the received input with respect to the proposed or current insured and (b) the third graphical representation. - View Dependent Claims (20, 21)
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Specification