Dimensionality reduction for content category data

• US 20070271286A1
• Filed: 05/16/2006
• Published: 11/22/2007
• Est. Priority Date: 05/16/2006
• Status: Abandoned Application

• Current Assignee: Sony Corporation (Sony Group Corp.), Sony Electronics Inc. (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.), Sony Electronics Inc. (Sony Group Corp.)
• Inventors: Plutowski, Mark, Purang, Khemdut
• Application Number:
  US11/435,448
• Publication Number:
  US 20070271286A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification

Abstract

The dimensionality of a content category dataset is reduced based on the categories and the relationship between the content and categories. The category dataset includes names of categories and relation data, where the relation data defines a relationship between the categories and content. The dimensionality of a category dataset is reduced by determining a number of subsets of the category dataset and generating new relation data, where the new relation data defines a relationship between the category dataset subsets and the content.

Claims

1. A computerized method comprising:

receiving a category dataset and a current relation data, wherein the category dataset comprises terms that describe a particular piece of content and the current relation data defines a relationship between the terms in the category dataset and the particular piece of content;

determining subsets of the category dataset, wherein a number of subsets is less than a number of terms in the category dataset, wherein each subset comprises at least one term;

generating new relation data, wherein the new relation data defines a new relationship between the subsets and the particular piece of content.

2. The computerized method of claim 1, further comprising replacing each subset with a generic term.

3. The computerized method of claim 1, wherein the subsets is determined using a frequency of occurrence for each term in the category data.

4. The computerized method of claim 1, further comprising:

grouping the terms into the subsets.

5. The computerized method of claim 1, further comprising:

generating a term hierarchy from the category data.

6. The computerized method of claim 5, further comprising:

splitting the term hierarchy according to a bound.

7. A machine readable medium comprising:

receiving a category dataset and a current relation data, wherein the category dataset comprises terms that describe a particular piece of content and the current relation data defines a relationship between the terms in the category dataset and the particular piece of content;

determining subsets of the category dataset, wherein a number of subsets is less than a number of terms in the category dataset, wherein each subset comprises at least one term;

generating new relation data, wherein the new relation data defines a new relationship between the subsets and the particular piece of content.

8. The machine readable medium of claim 7, further comprising replacing each subset with a generic term.

9. The machine readable medium of claim 7, wherein the subsets is determined using a frequency of occurrence for each term in the category data.

10. The machine readable medium of claim 7, further comprising:

grouping the terms into the subsets.

11. The machine readable medium of claim 7, further comprising:

generating a term hierarchy from the category data.

12. The machine readable medium of claim 11, further comprising:

splitting the term hierarchy according to a bound.

13. A apparatus comprising:

means for receiving a category dataset and a current relation data, wherein the category dataset comprises terms that describe a particular piece of content and the current relation data defines a relationship between the terms in the category dataset and the particular piece of content;

means for determining subsets of the category dataset, wherein a number of subsets is less than a number of terms in the category dataset, wherein each subset comprises at least one term;

means for generating new relation data, wherein the new relation data defines a new relationship between the subsets and the particular piece of content.

14. The apparatus of claim 13, further comprising:

means for grouping the terms into the subsets.

15. The apparatus of claim 13, further comprising:

means for generating a term hierarchy from the category data.

16. The apparatus of claim 15, further comprising:

means for splitting the term hierarchy according to a bound.

17. A system comprising:

a processor;

a memory coupled to the processor though a bus; and

a process executed from the memory by the processor to cause the processor to receive a category dataset and a current relation data, wherein the category dataset comprises terms that describe a particular piece of content and the current relation data defines a relationship between the terms in the category dataset and the particular piece of content, to determine subsets of the category dataset, wherein a number of subsets is less than a number of terms in the category dataset, wherein each subset comprises at least one term, to generate new relation data, wherein the new relation data defines a new relationship between the subsets and the particular piece of content.

18. The system of claim 17, wherein the process further causes the processor to group the terms into the subsets.

19. The system of claim 17, wherein the process further causes the processor to generate a term hierarchy from the category data.

20. The system of claim 19, wherein the process further causes the processor to split the term hierarchy according to a bound.