Automated knowledge base of feed tags

• US 20080005148A1
• Filed: 06/30/2006
• Published: 01/03/2008
• Est. Priority Date: 06/30/2006
• Status: Abandoned Application

• Current Assignee: Rearden Commerce Inc
• Original Assignee: Rearden Commerce Inc
• Inventors: Welch, Peter, Mortimore, William Charles
• Application Number:
  US11/478,799
• Publication Number:
  US 20080005148A1
• Time in Patent Office: Days
• US Class Current: 707/102
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/986 Document structures and storage, e.g. HTML extensions

Abstract

In one embodiment, a knowledge base is automatically built for enriching feeds coming from different sources and that have tags of different conventions, by deducting which tags go into various categories of knowledge.

Claims

1. ) A method comprising:

Reading data tags from a first data item received from a network connection;

Reading data tags from a second data item received from a network connection;

Identifying commonalities between the data tags of the first data item and the data tags of the second data item.

2. ) The method of claim 1, further comprising recording the commonalities of the data tags into pre-identified categories.

3. ) The method of claim 1, further comprising recording the commonalities of the data tags into a knowledge base of a database.

4. ) The method of claim 2, wherein the data tags of the first data item are from a first source, and the data tags of the second data item are from a second source.

5. ) The method of claim 3, further comprising, prior to identifying the commonalities, filtering the data tags of the first and second data item against at least one of, or a combination of, a deduction engines (DE), a meta directories (MD), and extraction and transformation languages (ETL).

6. ) The method of claim 4, further comprising categorizing the tags into pre-identified categories, based on the filtering.

7. ) The method of claim 6, further comprising generating one or more categories for categorizing the tags.

8. ) The method of claim 7, wherein the generating the one or more categories includes generating the one or more categories based on at least one of, or a combination of vertical databases, thesauruses, and alias tables.

9. ) The method of claim 4, further comprising adding data tags from the first data item to a third data item, the third data item matching the first data item.

10. ) The method of claim 9, wherein the third data item received from a third source.

11. ) The method of claim 10, wherein the third data item as received is exclusive of data tags.

12. ) A machine readable medium having stored thereon a set of instructions, which when executed perform a method comprising:

Reading data tags from a first data item received from a network connection;

Reading data tags from a second data item received from a network connection;

Identifying commonalities between the data tags of the first data item and the data tags of the second data item.

13. ) The machine readable medium of claim 12, further comprising recording the commonalities of the data tags into pre-identified categories.

14. ) The machine readable medium of claim 12, further comprising recording the commonalities of the data tags into a knowledge base of a database.

15. ) The machine readable medium of claim 13, wherein the data tags of the first data item are from a first source, and the data tags of the second data item are from a second source.

16. ) The machine readable medium of claim 15, further comprising, prior to identifying the commonalities, filtering the data tags of the first and second data item against at least one of, or a combination of, a deduction engines (DE), a meta directories (MD), and extraction and transformation languages (ETL).

17. ) The machine readable medium of claim 15, further comprising categorizing the tags into pre-identified categories, based on the filtering.

18. ) The machine readable medium of claim 17, further comprising generating one or more categories for categorizing the tags.

19. ) The machine readable medium of claim 18, wherein the generating the one or more categories includes generating the one or more categories based on at least one of, or a combination of vertical databases, thesauruses, and alias tables.

20. ) The machine readable medium of claim 15, further comprising adding data tags from the first data item to a third data item, the third data item matching the first data item.