System and method for improving resolution of channel data

• US 7,324,987 B2
• Filed: 09/24/2003
• Issued: 01/29/2008
• Est. Priority Date: 10/23/2002
• Status: Active Grant

• Current Assignee: Model N, Inc.
• Original Assignee: Infonow Corporation
• Inventors: Hsieh, Yuan Che, Kark, Donald, Rand, Nahum
• Primary Examiner(s): Wong; Don
• Assistant Examiner(s): FILIPCZYK, MARCIN R
• Application Number:
  US10/670,545
• Publication Number:
  US 20040083214A1
• Time in Patent Office: 1,588 Days
• Field of Search: 707 1- 7, 707/10, 707/100, 707/101, 707/200, 707/203, 705 75- 76, 705/1, 705/50, 705/51, 705/57
• US Class Current: 1/1
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99936 Pattern matching access

Abstract

A method for processing distribution channel data integrating business information with geographic data to produce integrated data, wherein the integrated data has greater resolution than the business information. Distribution channel data is captured and correlated with the integrated data to increase the resolution of the distribution channel data.

Claims

1. A system for managing a product distribution channel having a plurality of channel participants, comprising:

one or more reference record databases;

one or more reference records within the reference record databases, each reference record providing an association between business information and spatial data for a specific channel participant, wherein each reference record includes a reference record spatial identifier determined by geo-coding said spatial data;

transaction data related to at least one channel participant wherein said transaction data includes a transaction data spatial identifier determined by geo-coding spatial data associate with said transaction data;

a candidate identification mechanism for determining more than one candidate reference record from one of the reference record databases using both spatial and business data derived from the transaction data;

responsive to determining more than one candidate reference records, a matching mechanism for matching at least one candidate reference record from the determined more than one candidate reference records to the transaction data, wherein said matching mechanism includes a lexical matching process; and

storing in the reference record databases a match identifier associated with the match between the at least one candidate reference record from the determined more than one candidate reference records and the transaction data.

2. The system of claim 1 wherein at least one channel participant comprises a consumer of the product who receives the product from the distribution channel.

3. The system of claim 1 wherein at least one channel participant comprises a producer of the product who places the product in the distribution channel.

4. The system of claim 1 wherein at least one channel participant comprises a distributor of the product who receives the product from a producer and distributes the product to a consumer.

5. The system of claim 1 wherein at least one channel participant comprises a reseller such as a dealer, agent, or branch.

6. The system of claim 1 wherein the candidate identification mechanism further comprises a geo-coding mechanism operable to determine street-level spatial data from the transaction data.

7. The system of claim 6 wherein the candidate identification mechanism further comprises a selection mechanism for retrieving records that have spatial data substantially matching the spatial data obtained from the transaction record.

8. The system of claim 7 wherein the reference record comprises:

a reference identifier identifying the channel participant;

a business name; and

spatial information with predetermined accuracy.

9. The system of claim 8 wherein the predetermined accuracy is street-level accuracy.

10. The system of claim 8 wherein the predetermined accuracy is postal accuracy.

11. The system of claim 7 wherein the matching mechanism further comprises:

a lexical matching process operable to correlate non-spatial data in the transaction record with non-spatial data in the candidate reference records.

12. The system of claim 11 wherein the lexical matching process generates a score for each candidate reference record.

13. The system of claim 12 further comprising:

a selection process operable to select a candidate reference record based on the generated score exceeding a pre-selected threshold value, wherein the selected candidate reference record provides a precise identification of the at least one channel participant related to the transaction data.

14. The system of claim 13 wherein the selection process makes automated assignments to select candidates when the scores exceed a predetermined high threshold.

15. The system of claim 7 wherein the matching mechanism further comprises:

a lexical matching process operable to correlate spatial data in the transaction record with spatial data in the candidate reference records.

16. The system of claim 1 wherein the candidate identification mechanism determines postal code information from the transaction data.

17. The system of claim 1 wherein the candidate identification mechanism determines location information from the transaction data.

18. The system of claim 1 further comprising a learning database mechanism operable to hold records that create associations between information within transaction records that could not be automatically matched with reference records and the desired reference record so that subsequent transaction records can be matched with the desired reference records using the association provided by the learning database.

19. The system of claim 18 wherein the learning database is populated based on analysis of transaction records that require manual intervention to be associated with the desired reference record.

20. A method for identifying distribution channel participants comprising:

generating a transaction record comprising business and spatial data that identifies at least one channel participant with a first degree of precision;

geo-coding spatial data within the transaction record to determine a transaction spatial identifier for the transaction record;

providing a reference record database comprising a plurality of reference records wherein each reference record comprises business and spatial information having a second degree of precision, and wherein the second degree of precision is greater than the first degree of precision and each reference record is associated with a reference record spatial identifier, said reference record spatial identifier being determined by geo-coding spatial information within each reference record; and

determining at least one match between the transaction record and the plurality of reference records based on a comparative analysis of both lexical matching of transaction record business data to reference record business information and association of the transaction spatial identifier with reference record spatial identifiers, storing in the reference record database a match identifier associated with the at least one match between the transaction record and the plurality of reference records.

21. The method of claim 20 wherein the at least one channel participant is an end customer.

22. The method of claim 20 further comprising:

applying non-spatial matching processes to select one of the reference records and using the selected reference record to precisely identify the at least one channel participant.

23. The method of claim 20 further comprising:

using the one or more identified referenced records to attribute transactions to another channel participant, wherein the transaction record itself is has insufficient precision to accurately attribute the transactions.

24. The method of claim 20, wherein the transaction record includes information that identifies an entity in an imprecise manner that makes accurately matching of the transaction record to one of the reference records uncertain.

25. The method of claim 24, wherein the information in the transaction record comprises an identifier of an entity that includes a typographical error or another identifier not matching an entity identifier in the reference records.

26. The method of claim 24, wherein the information in the transaction record comprises business name or address information that does not match any business entity data in the reference records.

27. The method of claim 26, wherein the greater precision information in the references records includes as least a portion of the business name or address information in the transaction record that cannot be matched in the reference records.

28. The method of claim 24, wherein the information in the transaction record comprises an entity identifier for the entity that matches an entity identifier in the reference records and further includes location information that differs from location information in the reference records for the matched entity identifier, whereby imprecision in matching is introduced.

29. The method of claim 20 wherein the comparative analysis includes a first comparison and a second comparison, the first comparison comprising

identifying a plurality of reference records in the reference record database by associating the transaction spatial identifier with reference record spatial identifiers of the plurality of reference records, and

responsive to identifying the plurality of reference records, applying lexical matching to business information of each of the plurality of reference records and to the transaction record business data to identify a first matching reference record;

the second comparison comprising

identifying a plurality of reference records in the reference record database by applying lexical matching to business information of each reference record and to the transaction record business data, and

responsive to identifying the plurality of reference records, associating the transaction spatial identifier with spatial identifiers of each of the plurality of reference records to identify a second matching reference record; and

comparing the first matching reference record to the second matching reference record to determine a matched reference record.

30. The method of claim 20 wherein the comparative analysis includes

identifying a first plurality of reference records in the reference record database by associating the transaction spatial identifier with reference record spatial identifiers of the plurality of reference records, and

identifying a second plurality of reference records in the reference record database by applying lexical matching to business information of each reference record and to the transaction record business data;

selecting either the first plurality of reference records or the second plurality of reference records based on predetermined criteria;

responsive to selecting the first plurality of reference records, applying lexical matching to business information of each of the first plurality of reference records and to the transaction record business data to identify a matching reference record; and

responsive to selecting the second plurality of reference records, associating the transaction spatial identifier with spatial identifiers of each of the second plurality of reference records to identify a matching reference record.

31. A computer-based method for resolving ambiguous transaction records, comprising:

storing reference records in memory that each provide an association between business information and spatial data for each of a plurality of distribution channel participants, the spatial data including a geocode; and

with a resolver mechanism running on a computer having access to the memory, receiving a transaction record comprising transaction information and location information, wherein the transaction information includes an imprecise identification for one of the distribution channel participants associated with the stored reference records preventing a direct match with the business information and spatial data of the one distribution channel participants to be made with certainty;

responsive to failing to identify a direct match between the transaction record and the one distribution channel participant, operating the resolver mechanism to parse the location information in the transaction record and generate a geocode based on the parsed location information;

comparing the generated geocode with the reference record geocodes of each of the plurality of distribution channel participants to select one or more candidate reference records from the stored reference records;

performing lexical processing of the imprecise identification for one of the distribution channel participants with reference to the business information in the selected one or more candidate reference records; and

based on the lexical processing, matching the received transaction record to one of the selected one or more candidate reference records wherein a match identifier associated with the match between the received transaction record and one of the selected one or more candidate reference records is stored in memory.

32. The method of claim 31, wherein the geocodes comprise a value corresponding to a latitude and longitude location.

33. The method of claim 31, further comprising providing in memory a learning library comprising a set of previously received imprecise channel participant identifications and a matched one of the stored reference records and wherein the method further comprises prior to the matching based on the lexical processing comparing the imprecise identification for one of the distribution channel participants with the set of previously received imprecise channel participant identifications and matching the received transaction record when a match between the identifications is determined.