SIMILARITY MATCHING OF PRODUCTS BASED ON MULTIPLE CLASSIFICATION SCHEMES

• US 20090012971A1
• Filed: 01/31/2008
• Published: 01/08/2009
• Est. Priority Date: 01/26/2007
• Status: Active Grant

• Current Assignee: Information Resources Incorporated
• Original Assignee: Information Resources Incorporated
• Inventors: Johnson, Arvid C., Bergeon, Cheryl G., Hudson, Gregory David Neil, Basilico, Andrea, Gibbs, Marshall Ashby, Chapa, Craig Joseph, Yusko, Jay Alan, Griglione, Bradley Michael, Mason, Trevor, Hunt, Herbert Dennis, Agostinelli, Alberto, West, John Randall
• Granted Patent: US 9,262,503 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0623 Item investigation

Abstract

In embodiments of the present invention improved capabilities are described for identifying a first classification scheme associated with product attributes of a first grouping of products, identifying a second classification scheme associated with product attributes of a second grouping of products, and receiving a record of data relating to an item, the classification of which is uncertain. It may also involve receiving a dictionary of attributes associated with products and assigning the item to at least one of the classification schemes based on probabilistic matching among the attributes in the classification schemes, the attributes in the dictionary of attributes and the known attributes of the item.

Claims

1. A method comprising:

identifying a first classification scheme associated with product attributes of a first grouping of products;

identifying a second classification scheme associated with product attributes of a second grouping of products;

receiving a record of data relating to an item, the classification of which is uncertain;

receiving a dictionary of attributes associated with products; and

assigning the item to at least one of the classification schemes based on probabilistic matching among the attributes in the classification schemes, the attributes in the dictionary of attributes and the known attributes of the item.

2. The method of claim 1, further comprising iterating the probabilistic matching until a statistical criterion is met.

3. The method of claim 1, wherein the product attribute is a nutritional level.

4. The method of claim 1, wherein the product attribute is a brand.

5. The method of claim 1, wherein the product attribute is product category.

6. The method of claim 1, wherein the product attribute is based at least in part on a SKU.

7. The method of claim 1, wherein the product attribute is physical attribute.

8. The method of claim 7, wherein the physical attribute is a flavor.

9. The method of claim 7, wherein the physical attribute is a scent.

10. The method of claim 7, wherein the physical attribute is packaging type.

11. The method of claim 7, wherein the physical attribute is a product launch date.

12. The method of claim 7, wherein the physical attribute is display location.