Association of data with a product classification schema

• US 7,809,672 B1
• Filed: 06/28/2001
• Issued: 10/05/2010
• Est. Priority Date: 06/28/2001
• Status: Expired due to Fees

• Current Assignee: Blue Yonder Group, Inc. (Panasonic Holdings Corporation)
• Original Assignee: i2 Technologies US Incorporated (Panasonic Holdings Corporation)
• Inventors: Tenorio, Manoel
• Primary Examiner(s): Mofiz, Apu M
• Assistant Examiner(s): CHEN, TE Y
• Application Number:
  US09/895,525
• Time in Patent Office: 3,386 Days
• Field of Search: 707 1- 5, 707/101, 707/103, 707/10, 707/102, 707/2, 705/1, 705/26, 705/925, 705/934, 709/220, 709/213, 713/201, 706/46, 715/513
• US Class Current: 705/26.64
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0629 for generating comparisons
• CPC Class Codes: G06Q 30/08 Auctions

Abstract

A computer-implemented system (10) for associating target data with a product classification schema includes a data association module (39) that accesses the product classification schema. The schema includes a taxonomy that includes a hierarchy of classes into which products may be categorized. The schema further includes ontologies that are associated with one or more of the classes. Each ontology includes one or more product attributes. The data association module (39) accesses the target data to be associated with the schema and determines one or more classes with which at least a portion of the target data should be associated. This determination is based on a comparison between the target data and the product attributes of the ontologies or between the target data and values for one or more of the product attributes. Furthermore, the data association module (39) associates at least a portion of the target data with one or more classes in response to determining one or more classes with which at least a portion of the target data should be associated.

Claims

1. A computer-implemented system for categorizing product data in an electronic commerce transaction, the system comprising:

a global content directory server coupled with one or more seller databases over a network, the global content directory server comprising;

a storage medium stored therein a data association module configured to;

access a first product classification schema, the first schema comprising;

a taxonomy comprising a hierarchy of classes categorizing one or more products; and

ontology associated with one or more of the classes, each ontology comprising one or more product attributes, wherein each of the one or more products is associated with a global unique identifier;

access target data associated with the first schema, the target data organized according to a second product classification schema;

determine one or more classes of the first schema with which at least a portion of the target data is associated based on a comparison between the target data and the product attributes of the ontologies of the first schema or between the target data and values for one or more of the product attributes of the ontologies of the first schema, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated comprises using statistical correlation techniques to identify portions of the target data including values that correspond to values for a product attribute included in the ontologies of these one or more classes of the first schema;

associate the at least a portion of the target data with one or more classes of the first schema in response to determining, based on the comparison, the one or more classes of the first schema with which the at least a portion of the target data is associated; and

store the values for one or more of the product attributes of the ontologies of the first schema with which the target data is compared in the one or more seller databases.

2. The system of claim 1, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including the name or an equivalent name of a product attribute included in the ontologies of these one or more classes of the first schema.

3. The system of claim 1, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including values that match or are similar to values for a product attribute included in the ontologies of these one or more classes of the first schema.

4. The system of claim 1, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including a range of values that matches or is similar to a range of values for a product attribute included in the ontologies of these one or more classes of the first schema.

5. The system of claim 1, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including symbols that match or are similar to symbols associated with values for a product attribute included in the ontologies of these one or more classes of the first schema.

6. The system of claim 1, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data having formatting that matches or is similar to formatting of values for a product attribute included in the ontologies of these one or more classes of the first schema.

7. The system of claim 1, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises using vector space analysis to identify multiple portions of the target data including values that correspond to values for multiple product attributes included in the ontologies of these one or more classes of the first schema.

8. The system of claim 1, wherein the values in the seller databases identified by one or more pointers associated with one or more classes of the first schema.

9. The system of claim 1, wherein associating the at least a portion of the target data with one or more classes of the first schema comprises associating one or more pointers to the target data with the one or more classes of the first schema.

10. The system of claim 1, wherein associating the at least a portion of the target data with one or more classes of the first schema comprises associating one or more pointers to specific portions of the target data with one or more product attributes included in the ontology of the one or more classes of the first schema.

11. A computer-implemented method for categorizing product data in an electronic commerce transaction, the method comprising:

accessing, by a global content directory server, a first product classification schema, the first schema comprising a taxonomy comprising a hierarchy of classes categorizing one or more products, the first schema further comprising ontologies associated with one or more of the classes, each ontology comprising one or more product attributes, wherein each of the one or more products is associated with a global unique identifier;

accessing, by the server, target data associated with the first schema, the target data organized according to a second product classification schema;

determining, by the server, one or more classes of the first schema with which at least a portion of the target data is associated based on a comparison between the target data and the product attributes of the ontologies of the first schema or between the target data and values for one or more of the product attributes of the ontologies of the first schema, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated comprises using statistical correlation techniques to identify portions of the target data including values that correspond to values for a product attribute included in the ontologies of these one or more classes of the first schema;

associating, by the server, the at least a portion of the target data with one or more classes of the first schema in response to determining, based on the comparison, the one or more classes of the first schema with which the at least a portion of the target data is associated; and

storing, by the server, the values for one or more of the product attributes of the ontologies of the first schema with which the target data is compared in one or more seller databases.

12. The method of claim 11, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including the name or an equivalent name of a product attribute included in the ontologies of these one or more classes of the first schema.

13. The method of claim 11, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including values that match or are similar to values for a product attribute included in the ontologies of these one or more classes of the first schema.

14. The method of claim 11, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including a range of values that matches or is similar to a range of values for a product attribute included in the ontologies of these one or more classes of the first schema.

15. The method of claim 11, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including symbols that match or are similar to symbols associated with values for a product attribute included in the ontologies of these one or more classes of the first schema.

16. The method of claim 11, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data having formatting that matches or is similar to formatting of values for a product attribute included in the ontologies of these one or more classes of the first schema.

17. The method of claim 11, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises using vector space analysis to identify multiple portions of the target data including values that correspond to values for multiple product attributes included in the ontologies of these one or more classes of the first schema.

18. The method of claim 11, wherein the values in the seller databases identified by one or more pointers associated with one or more classes of the first schema.

19. The method of claim 11, wherein associating the at least a portion of the target data with one or more classes of the first schema comprises associating one or more pointers to the target data with the one or more classes of the first schema.

20. The method of claim 11, wherein associating the at least a portion of the target data with one or more classes of the first schema comprises associating one or more pointers to specific portions of the target data with one or more product attributes included in the ontology of the one or more classes of the first schema.

21. Software for categorizing product data in an electronic commerce transaction, the software embodied in a computer-readable storage medium and when executed using one or more computers is configured to:

access a first product classification schema, the first schema comprising a taxonomy comprising a hierarchy of classes categorizing one or more products, the first schema further comprising ontologies associated with one or more of the classes, each ontology comprising one or more product attributes, wherein each of the one or more products is associated with a global unique identifier and provided by a global content directory server;

access target data associated with the first schema, the target data organized according to a second product classification schema;

determine one or more classes of the first schema with which at least a portion of the target data is associated based on a comparison between the target data and the product attributes of the ontologies of the first schema or between the target data and values for one or more of the product attributes of the ontologies of the first schema, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated comprises using statistical correlation techniques to identify portions of the target data including values that correspond to values for a product attribute included in the ontologies of these one or more classes of the first schema;

associate the at least a portion of the target data with one or more classes of the first schema in response to determining, based on the comparison, the one or more classes of the first schema with which the at least a portion of the target data is associated; and

store the values for one or more of the product attributes of the ontologies of the first schema with which the target data is compared in one or more seller databases.

22. The software of claim 21, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including the name or an equivalent name of a product attribute included in the ontologies of these one or more classes of the first schema.

23. The software of claim 21, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including values that match or are similar to values for a product attribute included in the ontologies of these one or more classes of the first schema.

24. The software of claim 21, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including a range of values that matches or is similar to a range of values for a product attribute included in the ontologies of these one or more classes of the first schema.

25. The software of claim 21, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data including symbols that match or are similar to symbols associated with values for a product attribute included in the ontologies of these one or more classes of the first schema.

26. The software of claim 21, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises identifying a portion of the target data having formatting that matches or is similar to formatting of values for a product attribute included in the ontologies of these one or more classes of the first schema.

27. The software of claim 21, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated further comprises using vector space analysis to identify multiple portions of the target data including values that correspond to values for multiple product attributes included in the ontologies of these one or more classes of the first schema.

28. The software of claim 21, wherein the values in the seller databases identified by one or more pointers associated with one or more classes of the first schema.

29. The software of claim 21, wherein associating the at least a portion of the target data with one or more classes of the first schema comprises associating one or more pointers to the target data with the one or more classes of the first schema.

30. The software of claim 21, wherein associating the at least a portion of the target data with one or more classes of the first schema comprises associating one or more pointers to specific portions of the target data with one or more product attributes included in the ontology of the one or more classes of the first schema.

31. A computer-implemented system for categorizing product data in an electronic commerce transaction, the system comprising:

a global content directory server coupled with one or more seller databases over a network, the global content directory server comprising;

a storage medium stored therein a data association module configured to;

access a first product classification schema, the first schema comprising a taxonomy comprising a hierarchy of classes categorizing one or more products, the first schema further comprising ontologies associated with one or more of the classes, each ontology comprising one or more product attributes, wherein each of the one or more products is associated with a global unique identifier;

access target data associated with the first schema, the target data organized according to a second product classification schema;

determine one or more classes of the first schema with which at least a portion of the target data is associated based on a comparison between the target data and the product attributes of the ontologies of the first schema or between the target data and values for one or more of the product attributes of the ontologies of the first schema, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated comprises using statistical correlation techniques to identify portions of the target data including values that correspond to values for a product attribute included in the ontologies of these one or more classes of the first schema;

associate the at least a portion of the target data with one or more classes of the first schema in response to determining, based on the automatic comparison, the one or more classes of the first schema with which the at least a portion of the target data is associated, the target data associated with the classes of the first schema using one or more pointers to the target data; and

store the values for one or more of the product attributes of the ontologies of the first schema with which the target data is compared in the one or more seller databases.

32. A computer-implemented method for categorizing product data in an electronic commerce transaction, the method comprising:

accessing, by a global content directory server, a first product classification schema, the first schema comprising a taxonomy comprising a hierarchy of classes categorizing one or more products, the first schema further comprising ontologies associated with one or more of the classes, each ontology comprising one or more product attributes, wherein each of the one or more products is associated with a global unique identifier;

accessing, by the server, target data associated with the first schema, the target data organized according to a second product classification schema;

determining, by the server, one or more classes of the first schema with which at least a portion of the target data is associated based on a comparison between the target data and the product attributes of the ontologies of the first schema or between the target data and values for one or more of the product attributes of the ontologies of the first schema, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated comprises using statistical correlation techniques to identify portions of the target data including values that correspond to values for a product attribute included in the ontologies of these one or more classes of the first schema;

associating, by the server, the at least a portion of the target data with one or more classes of the first schema in response to determining, based on the comparison, the one or more classes of the first schema with which the at least a portion of the target data is associated, the target data associated with the classes of the first schema using one or more pointers to the target data; and

storing, by the server, the values for one or more of the product attributes of the ontologies of the first schema with which the target data is compared in one or more seller databases.

33. Software for categorizing product data in an electronic commerce transaction, the software embodied in a computer-readable storage medium and when executed using one or more computers is configured to:

access a first product classification schema, the first schema comprising a taxonomy comprising a hierarchy of classes categorizing one or more products, the first schema further comprising ontologies associated with one or more of the classes, each ontology comprising one or more product attributes, wherein each of the one or more products is associated with a global unique identifier and provided by a global content directory server;

access target data associated with the first schema, the target data organized according to a second product classification schema;

determine one or more classes of the first schema with which at least a portion of the target data is associated based on a comparison between the target data and the product attributes of the ontologies of the first schema or between the target data and values for one or more of the product attributes of the ontologies of the first schema, wherein determining one or more classes of the first schema with which the at least a portion of the target data is associated comprises using statistical correlation techniques to identify portions of the target data including values that correspond to values for a product attribute included in the ontologies of these one or more classes of the first schema;

associate the at least a portion of the target data with one or more classes of the first schema in response to determining, based on the comparison, the one or more classes of the first schema with which at the least a portion of the target data is associated, the target data associated with the classes of the first schema using one or more pointers to the target data; and

store the values for one or more of the product attributes of the ontologies of the first schema with which the target data is compared in one or more seller databases.