DATA CLASSIFICATION METHODS AND APPARATUS FOR USE WITH DATA FUSION

• US 20070198573A1
• Filed: 03/28/2007
• Published: 08/23/2007
• Est. Priority Date: 09/28/2004
• Status: Active Grant

• Current Assignee: Nielsen Company (US), LLC
• Original Assignee: Nielsen Company (US), LLC
• Inventors: Samson, Jerome, McMillan, Francis
• Granted Patent: US 7,516,111 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Methods and apparatus for classifying data for use in data fusion processes are disclosed. An example method of classifying data identifies classification tree information and assigns values to each of a plurality of nodes associated with the classification tree information. Each of the values is indicative of a relationship between its respective node and one of a plurality of classes. The example method also assigns each node to one of the classes based on a comparison of at least two of the assigned values and classifies the data based on the assignment of the nodes to the classes.

Claims

1. A method of classifying data, comprising:

assigning values to each of a plurality of nodes associated with a classification tree, wherein each of the values is indicative of a relationship between its respective node and one of a plurality of classes;

assigning each node of the classification tree to one of the classes based on a comparison of at least two of the assigned values; and

classifying the data based on the classification tree and the assignment of the nodes to the classes.

2. A method as defined in claim 1, further comprising retrieving values representative of the classification tree from a memory.

3. A method as defined in claim 1, wherein assigning the values to each of the nodes includes assigning a plurality of values to each of the nodes, wherein each of the plurality of values corresponds to only one of the classes.

4. A method as defined in claim 2, wherein assigning the plurality of values to each of the nodes includes generating the plurality of values based on a frequency distribution of the classes for each of the nodes.

5. A method as defined in claim 4, wherein generating the plurality of values based on the frequency distribution of the classes includes calculating an index value based on a frequency distribution of the classes within an overall population associated with the classification tree.

6. A method as defined in claim 1, wherein assigning each node to only one of the classes based on the comparison of the at least two of the assigned values includes assigning one of a plurality of class codes to each node so that at least two nodes have the same class code.

7. A method as defined in claim 1, wherein assigning each node to only one of the classes includes assigning the nodes to the classes so that relatively larger node values determine the class to which each node is assigned.

8. A method as defined in claim 1, wherein assigning each node to only one of the classes includes re-assigning at least one of the nodes.

9. A method as defined in claim 1, wherein the classes are usage or consumption classes.

10. A method as defined in claim 1, further comprising fusing the classified data records based on classification information associated with the classified data records.

11. An apparatus for classifying data, comprising:

a memory; and

a processor coupled to the memory and configured to;

assign values to each of a plurality of nodes associated with a classification tree, wherein each of the values is indicative of a relationship between its respective node and one of a plurality of classes;

assign each node of the classification tree to one of the classes based on a comparison of at least two of the assigned values; and

classify the data based on the classification tree and the assignment of the nodes to the classes.

12. An apparatus as defined in claim 11, wherein the processor is configured to retrieve values representative of the classification tree from a memory.

13. An apparatus as defined in claim 11, wherein the processor is configured to assign the values to each of the nodes by assigning a plurality of values to each of the nodes, wherein each of the plurality of values corresponds to only one of the classes.

14. An apparatus as defined in claim 13, wherein the processor is configured to assign the plurality of values to each of the nodes by generating the plurality of values based on a frequency distribution of the classes for each of the nodes.

15. An apparatus as defined in claim 14, wherein the processor is configured to generate the plurality of values based on the frequency distribution of the classes by calculating an index value based on a frequency distribution of the classes within an overall population associated with the classification tree.

16. An apparatus as defined in claim 11, wherein the processor is configured to assign each node to only one of the classes based on the comparison of the at least two of the values by assigning one of a plurality of class codes to each node so that at least two nodes have the same class code.

17. An apparatus as defined in claim 11, wherein the processor is configured to assign each node to only one of the classes by assigning the nodes to the classes so that relatively larger node values determine the class to which each node is assigned.

18. An apparatus as defined in claim 11, wherein the processor is configured to assign each node to only one of the classes by re-assigning at least one of the nodes.

19. An apparatus as defined in claim 11, wherein the classes are usage or consumption classes.

20. An apparatus as defined in claim 11, wherein the processor is configured to fuse the classified data records based on classification information associated with the classified data records.

21. A machine accessible medium having instructions stored thereon that, when executed, cause a machine to:

assign values to each of a plurality of nodes associated with a classification tree, wherein each of the values is indicative of a relationship between its respective node and one of a plurality of classes;

assign each node of the classification tree to one of the classes based on a comparison of at least two of the assigned values; and

classify data based on the classification tree and the assignment of the nodes to the classes.

22-59. -59. (canceled)