CATEGORIZING OBJECTS, SUCH AS DOCUMENTS AND/OR CLUSTERS, WITH RESPECT TO A TAXONOMY AND DATA STRUCTURES DERIVED FROM SUCH CATEGORIZATION

• US 20120259856A1
• Filed: 06/20/2012
• Published: 10/11/2012
• Est. Priority Date: 04/22/2005
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: GEHRKING, David, LAW, Ching, MAXWELL, Andrew
• Granted Patent: US 8,918,395 B2
• Time in Patent Office: Days
• US Class Current: 707/739
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

A Website may be automatically categorized by (a) accepting Website information, (b) determining a set of scored clusters (e.g., semantic, term co-occurrence, etc.) for the Website using the Website information, and (c) determining at least one category (e.g., a vertical category) of a predefined taxonomy using at least some of the set of clusters.

Claims

1. A computer-implemented method to associate a semantic cluster with one or more categories of a predefined taxonomy, the method comprising:

a) accepting, by a computer system including at least one computer, a semantic cluster;

b) identifying, by the computer system, a set of a one or more scored concepts using the accepted cluster;

c) identifying, by the computer system, a set of one or more categories using at least some of the one or more scored concepts; and

d) associating, by the computer system, at least some of the one or more categories with the semantic cluster.

2. The computer-implemented method of claim 1 wherein the semantic cluster is a term co-occurrence cluster.

3. The computer-implemented method of claim 1 wherein the semantic cluster includes terms that tend to co-occur in a search session on a search engine.

4. The computer-implemented method of claim 1 wherein the semantic cluster includes terms that tend to co-occur in documents available on the World Wide Web.

5. The computer-implemented method of claim 1 wherein the act of associating at least some of the one or more categories with the semantic cluster includes generating and storing an index entry which maps the semantic cluster to each of the at least some of the one or more categories.

6. The computer-implemented method of claim 1 wherein categories of the predefined taxonomy correspond to at least one of (A) related products that are likely to be found in Website content, (B) related services that are likely to be found in Website content, (C) related industries that are likely to be found in Website content, and (D) related topics that are likely to be found in Website content.

7. A computer-implemented method to associate a property with one or more categories of a predefined taxonomy, the method comprising:

a) accepting, by a computer system including at least one computer, information about the property;

b) identifying, by the computer system, a set of a one or more scored semantic clusters using the accepted property information;

c) identifying, by the computer system, a set of one or more categories using at least some of the one or more scored semantic clusters; and

d) associating, by the computer system, at least some of the one or more categories with the property.

8. The computer-implemented method of claim 7 wherein the property is a Webpage.

9. The computer-implemented method of claim 7 wherein the property is a Website including a plurality of Webpages.

10. The computer-implemented method of claim 7 wherein the act of associating at least some of the one or more categories with the property includes generating and storing an index entry which maps property information to each of the at least some of the one or more categories.

11. The computer-implemented method of claim 7 wherein categories of the predefined taxonomy correspond to at least one of (A) related products that are likely to be found in Website content, (B) related services that are likely to be found in Website content, (C) related industries that are likely to be found in Website content, (D) related topics that are likely to be found in Website content, and (E) related content formats that are likely to be found in Website content.

12. A machine-readable medium having stored thereon machine-readable information comprising a plurality of entries, each entry including semantic cluster information and information identifying one or more associated categories of a predefined taxonomy.

13. The machine-readable medium of claim 12 wherein categories of the predefined taxonomy correspond to at least one of (A) related products that are likely to be found in Website content, (B) related services that are likely to be found in Website content, (C) related industries that are likely to be found in Website content, (D) related topics that are likely to be found in Website content, and (E) related content formats that are likely to be found in Website content.

14. The machine-readable medium of claim 12 wherein the semantic cluster is a term co-occurrence cluster.

15. The machine-readable medium of claim 12 wherein the semantic cluster includes terms that tend to co-occur in a search session on a search engine.

16. The machine-readable medium of claim 12 wherein the semantic cluster includes terms that tend to co-occur in documents available on the World Wide Web.