Categorizing objects, such as documents and/or clusters, with respect to a taxonomy and data structures derived from such categorization

• US 20060242147A1
• Filed: 04/22/2005
• Published: 10/26/2006
• Est. Priority Date: 04/22/2005
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Law, Ching, Maxwell, Andrew, Gehrking, David
• Granted Patent: US 8,229,957 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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. A semantic cluster (e.g., a term co-occurrence cluster) may be automatically associated with one or more categories (e.g., vertical categories) of a predefined taxonomy by (a) accepting a semantic cluster, (b) identifying a set of a one or more scored concepts using the accepted cluster, (c) identifying a set of one or more categories using at least some of the one or more scored concepts, and (d) associating at least some of the one or more categories with the semantic cluster. A property (e.g., a Website) may be associated with one or more categories (e.g., vertical categories) of a predefined taxonomy by (a) accepting information about the property, (b) identifying a set of a one or more scored semantic clusters (e.g., term co-occurrence clusters) using the accepted property information, (c) identifying a set of one or more categories (e.g., vertical categories) using at least some of the one or more scored semantic clusters, and (d) associating at least some of the one or more categories with the property.

Claims

1. A computer-implemented method for automatically categorizing a Website, the method comprising:

a) accepting Website information;

b) determining a set of scored clusters for the Website using the Website information; and

c) determining at least one category of a predefined taxonomy using at least some of the set of clusters.

2. The computer-implemented method of claim 1 wherein the act determining a set of scored clusters for the Website using the Website information uses pageviews and activation scores on individual Webpages of the Website.

3. The computer implemented method of claim 1 wherein the act of determining at least one category of a predefined taxonomy using at least some of the clusters includes

i) determining a set of one or more concepts using the set of scored clusters, and

ii) determining the at least one category using at least some of the set of one or more concepts.

4. The computer implemented method of claim 1 wherein the act of determining at least one category of a predefined taxonomy using at least some of the clusters includes using information of the at least some of the clusters to look up one or more categories.

5. The computer-implemented method of claim 4 wherein the predefined taxonomy is hierarchical, and

wherein the act of determining at least one category of a predefined taxonomy using at least some of the clusters further includes,

for at least some of the one or more categories, determining a score including (1) an intra-category cluster score of the category, and (2) intra-category cluster scores of categories that are descendants of the category in the hierarchical taxonomy.

6. The computer-implemented method of claim 5 wherein the act of determining at least one category of a predefined taxonomy using at least some of the clusters further includes,

determining a deepest hierarchical level category having a determined score which is greater than a predetermined threshold.

7. 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, (D) related topics that are likely to be found in Website content, and (E) related content formats (such as forums, blogs, etc.) that are likely to be found in Website content.

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

a) accepting a semantic cluster;

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

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

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

9. The computer-implemented method of claim 8 wherein the semantic cluster is a term co-occurrence cluster.

10. The computer-implemented method of claim 8 wherein the semantic cluster includes terms that tend to co-occur in a search session on a search engine.

11. The computer-implemented method of claim 8 wherein the semantic cluster includes terms that tend to co-occur in documents available on the World Wide Web.

12. The computer-implemented method of claim 8 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.

13. The computer-implemented method of claim 8 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.

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

a) accepting information about the property;

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

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

d) associating at least some of the one or more categories with the property.

15. The computer-implemented method of claim 14 wherein the property is a Webpage.

16. The computer-implemented method of claim 14 wherein the property is a Website including a plurality of Webpages.

17. The computer-implemented method of claim 14 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.

18. The computer-implemented method of claim 14 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.

19. 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.

20. The machine-readable medium of claim 19 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.

21. The machine-readable medium of claim 19 wherein the semantic cluster is a term co-occurrence cluster.

22. The machine-readable medium of claim 19 wherein the semantic cluster includes terms that tend to co-occur in a search session on a search engine.

23. The machine-readable medium of claim 19 wherein the semantic cluster includes terms that tend to co-occur in documents available on the World Wide Web.

24. Apparatus for automatically categorizing a Website, the apparatus comprising:

a) means for accepting Website information;

b) means for determining a set of scored clusters for the Website using the Website information; and

c) means for determining at least one category of a predefined taxonomy using at least some of the set of clusters.

25. Apparatus for associating a semantic cluster with one or more categories of a predefined taxonomy, the apparatus comprising:

a) means for accepting a semantic cluster;

b) means for identifying a set of a one or more scored concepts using the accepted cluster;

c) means for identifying a set of one or more categories using at least some of the one or more scored concepts; and

d) means for associating at least some of the one or more categories with the semantic cluster.

26. Apparatus for associating a property with one or more categories of a predefined taxonomy, the apparatus comprising:

a) means for accepting information about the property;

b) means for identifying a set of a one or more scored semantic clusters using the accepted property information;

c) means for identifying a set of one or more categories using at least some of the one or more scored semantic clusters; and

d) means for associating at least some of the one or more categories with the property.