Computer system and method of data analysis
First Claim
1. A data comparison system for comparing data stored within a database against each other to determine at least one of duplicate, fraudulent, defective and irregular data, said data comparison system comprising:
- a database storing data therein;
a pattern database storing pattern data therein;
a data pattern build system, responsively connected to said database and to said pattern database, retrieving the data from said database and generating the pattern data formatted in accordance a predetermined patten, the predetermined pattern comprising an array having array locations corresponding to each character in a defined character set, said data pattern build system incrementing a value in each of the array locations responsive to the number of occurrences of each character in the data and storing the array as the pattern data in said pattern database; and
a neural network, responsively connected to said pattern database, retrieving the pattern data stored therein and comparing the pattern data to each other and determining responsive to the comparing when different pattern data match in accordance with predetermined criteria indicating that the different pattern data are at least one of duplicate, fraudulent, defective and irregular.
2 Assignments
0 Petitions
Accused Products
Abstract
A neural network based data comparison system compares data stored within a database against each other to determine duplicative, fraudulent, defective and/or irregular data. The system includes a database storing data therein, and a pattern database storing pattern data therein. The system further includes a data pattern build system, responsively connected to the database and to the pattern database. The data pattern build system retrieves the data from the database and generates the pattern data formatted in accordance a predetermined patten. The predetermined pattern includes an array having array locations corresponding to each character in a defined character set. The data pattern build system increments a value in each of the array locations responsive to the number of occurrences of each character in the data and stores the array as the pattern data in the pattern database. The comparison system also includes a neural network, responsively connected to the pattern database, which retrieves the pattern data stored therein and compares the pattern data to each other and determines responsive to the comparing when different pattern data match in accordance with predetermined criteria indicating that the different pattern data are duplicative, fraudulent, defective and/or irregular.
94 Citations
16 Claims
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1. A data comparison system for comparing data stored within a database against each other to determine at least one of duplicate, fraudulent, defective and irregular data, said data comparison system comprising:
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a database storing data therein; a pattern database storing pattern data therein; a data pattern build system, responsively connected to said database and to said pattern database, retrieving the data from said database and generating the pattern data formatted in accordance a predetermined patten, the predetermined pattern comprising an array having array locations corresponding to each character in a defined character set, said data pattern build system incrementing a value in each of the array locations responsive to the number of occurrences of each character in the data and storing the array as the pattern data in said pattern database; and a neural network, responsively connected to said pattern database, retrieving the pattern data stored therein and comparing the pattern data to each other and determining responsive to the comparing when different pattern data match in accordance with predetermined criteria indicating that the different pattern data are at least one of duplicate, fraudulent, defective and irregular. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. In a data comparison system for comparing data stored within a repository against each other to determine at least one of duplicate, fraudulent, defective and irregular data, the data comparison system comprising a database storing data therein, a pattern database storing pattern data therein, a data pattern build system and a neural network, a method of comparing the data stored within the database against each other to determine at least one of duplicate, fraudulent, defective and irregular data, said method comprising the steps of:
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(a) retrieving the data from the database; (b) generating pattern data formatted in accordance a predetermined pattern from the data, the predetermined pattern comprising an array having array locations corresponding to each character in a defined character set, said generating the pattern data comprising the step of incrementing a value in each of the array locations responsive to the number of occurrences of each character in the data; (d) storing the array as the pattern data; and (e) retrieving the pattern data and comparing the pattern data to each other; and (f) determining responsive to said comparing when different pattern data match in accordance with predetermined criteria indicating that the different pattern data are at least one of duplicate, fraudulent, defective and irregular.
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13. A computer based system for examining data stored electronically in a database of a computer, wherein the database stores records each having a one or more fields, comprising:
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accessing means for accessing criteria stored in the computer, wherein the criteria includes the number of items stored in the database to be examined; sample generation means for generating a sample set of data based on the criteria, such that said sample set of data includes at least the number of items to be examined in accordance with the criteria, wherein said sample set of data is selected by applying at least one of a focus group criteria, a filter criteria, a skew criteria, or an empty field indicator, wherein said sample generation means includes at least one of focus group means, responsive to said focus group criteria, for logically organizing a variety of fields within the database whose combined accuracy are analyzed as one unit, filter means, responsive to said filter criteria, for determining records and fields for inclusion in said sample set, empty field means, responsive to said empty field indicator, for not including empty fields in said sample set when said sample set is generated, and skew means, responsive to said skew criteria, for emphasizing one or more fields within a record such that said sample set is biased towards said emphasized one or more fields, but does not limit said sample set to only emphasized fields; and analysis means for accepting said errors, and determining results, said results indicating approximate accuracy values of said the records stored in said database. - View Dependent Claims (14, 15, 16)
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Specification