System and method for regular expression generation for improved data transfer

Abstract

A system and method for generating regular expressions to identify vendors to enable improved financial data transfer from a first computer system to a second computer system is provided.

What is claimed is: 
     
         1 . A method for vendor identification for received transaction data, the method comprising the steps of:
 receiving, at a computer system comprising a processor and a memory, new transaction data associated with an unknown vendor;   comparing, by the computer system, the new transaction data with one or more regular expressions for each of a plurality of known vendors,
 wherein the one or more regular expression for each of the plurality of known vendors is stored in a vendor data structure, and 
 wherein each of the one or more regular expressions is unique in the vendor data structure and determined to be unique utilizing a clustering technique that generates a different number of clusters for historical data until the regular expression is determined to be unique in the vendor data structure; 
   determining, by the computer system, whether a single regular expression, of the one or more regular expressions for each of the plurality of known vendors, matches the new transaction data;   in response to a match between the single regular expression and the new transaction data, determining that a corresponding vendor, corresponding to the single regular expression, is the unknown vendor; and   in response to no match between the one or more regular expressions, for each of the plurality of known vendors, and the new transaction data:   determining that input is required to identify the unknown vendor,   receiving the input identifying the unknown vendor as a particular vendor, and   updating the vendor data structure with a new entry that associates the f new transaction data with the particular vendor.   
     
     
         2 . The method of  claim 1  wherein processing throughput, at the computer system, increases based on determining the corresponding vendor or identifying the particular vendor. 
     
     
         3 . The method of  claim 1  wherein the clustering technique is based on a Levenshtein distance. 
     
     
         4 . The method of  claim 1  wherein the new transaction data comprises credit card transactions. 
     
     
         5 . A system comprising:
 a computer having a processor, the processor executing a transaction management software, the transaction management software configured to:   receive, over a network, new transaction data associated with an unknown vendor;   compare the new transaction data with one or more regular expressions for each of a plurality of known vendors, wherein the one or more regular expression for each of the plurality of known vendors is stored in a vendor data structure;   determine whether a single regular expression, of the one or more regular expressions for each of the plurality of known vendors, matches the new transaction data;   in response to a match between a single regular expression and the new transaction data, determine that a corresponding vendor, corresponding to the single regular expression, is the unknown vendor; and   in response to no match between the one or more regular expressions, for each of the plurality of known vendors, and the new transaction data:
 determine that input is required to identify the unknown vendor, 
 receive the input identifying the unknown vendor as a particular vendor, and 
 update the vendor data structure with a new entry that associates the new transaction data with the particular vendor. 
   
     
     
         6 . The system of  claim 5  wherein processing throughput, at the system, increases based on determining the corresponding vendor or identifying the particular vendor to increases based on the identifying the identified vendor or determining the particular vendor. 
     
     
         7 . The system of  claim 5  wherein each of the one or more regular expressions, generated for each of the plurality of known vendors, is unique within the vendor data structure and generated using a clustering technique. 
     
     
         8 . The system of  claim 7  wherein the clustering technique is based on a Levenshtein distance. 
     
     
         9 . The method of  claim 5  wherein the new transaction data comprises credit card transactions.