Discovering relevant concept and context for content node

1. A computerized method comprising:

obtaining a browsing history of a user from a web browser of a user device and generating a concept map of the browsing history comprising concepts as nodes and links between the nodes indicating relationships among the concepts;

opening a web page via the web browser, the web page comprising a plurality of different predefined content sections;

identifying a plurality of concept candidates to be added to the concept map from the plurality of different predefined content sections;

ranking, by a concept filterer, the plurality of concept candidates to create a ranked plurality of concept candidates based on concept nodes included in the concept map;

expanding, by a concept expander, the ranked plurality of concept candidates according to one or more cost functions, the expanding creating an expanded set of concepts after ranking the plurality of concept candidates; and

augmenting, in a memory, one or more of nodes and links within the concept map based on the expanded set of concepts.

2. The method of claim 1 , wherein the identifying is based at least in part on one or more statistical measures, wherein the one or more statistical measures comprises one or more of:

an indication of a likelihood that a given n-gram will appear in a document that is part of a corpus;

a frequency of n-grams in the web page;

a similarity of the web page to other web pages for which relevant concept candidates have already been identified; and

a weight of the web page in the concept map.

3. The method of claim 1 , wherein the ranking is based on one or more of:

a frequency that the one or more concept candidates occurs in the web page;

a likelihood of the one or more concept candidates appearing in a document; and

a likelihood of the one or more concept candidates being selected based on a closeness of the web page to similar web pages.

4. The method of claim 1 , wherein the concept map is derived from one or more of:

concept relationships found on the World Wide Web;

associations derived from user browsing history;

advertisers bidding campaigns;

taxonomies; and

encyclopedias.

5. The method of claim 1 , wherein the web page comprises a content node that includes a user query having a set of search keywords.

6. The method of claim 1 , wherein one or more concept candidates are provided by a user.

7. The method of claim 1 , wherein the augmenting comprises selecting neighbor nodes that are more likely to be strongly associated with each other based on one or more cost functions.

8. The method of claim 7 , wherein the one or more cost functions comprises selecting neighbor nodes that, based on aggregate user activity history, have a higher likelihood to be associated.

9. The method of claim 7 , wherein the one or more cost functions comprises determining which neighboring concepts in the concept map are tied to a form of monetization that yields a highest conversion rate.

10. The method of claim 1 , further comprising mapping one or more advertisements to the web page based at least in part on the expanded set of concepts.

11. An apparatus comprising:

a memory; and

a processor coupled to the memory and configured to:

obtain a browsing history of a user from a web browser of a user device and generating a concept map of the browsing history comprising concepts as nodes and links between the nodes indicating relationships among the concepts;

open a web page via the web browser, the web page comprising a plurality of different predefined content sections;

identify a plurality of concept candidates to be added to the concept map from the plurality of different predefined content sections,

rank the plurality of concept candidates to create a ranked plurality of concept candidates based on concept nodes included in the concept map; and

expand the ranked plurality of concept candidates according to one or more cost functions, wherein an expanded set of concepts is created after ranking the plurality of concept candidates, and

augment one or more of nodes and links within the concept map based on the expanded set of concepts.

12. The apparatus of claim 11 , wherein the processor identifies the plurality of concept candidates based at least in part on one or more statistical measures, wherein the one or more statistical measures comprises one or more of:

an indication of a likelihood that a given n-gram will appear in a document that is part of a corpus;

a frequency of n-grams in the web page;

a similarity of the web page to other web pages for which relevant concept candidates have already been identified; and

a weight of the web page in the concept map.

13. The apparatus of claim 11 , wherein the ranking is based on one or more of:

a frequency that the one or more concept candidates occurs in the web page;

a likelihood of the one or more concept candidates appears in a document; and

a likelihood of the one or more concept candidates being selected based on a closeness of the web page to similar web pages.

14. The apparatus of claim 11 , wherein the concept association map is derived from one or more of:

concept relationships found on the World Wide Web;

associations derived from user browsing history;

advertisers bid campaigns;

taxonomies; and

encyclopedias.

15. The apparatus of claim 11 , wherein the web page comprises a content node that includes a user query having a set of search keywords.

16. The apparatus of claim 11 , wherein one or more concept candidates are provided by a user.

17. The apparatus of claim 11 , wherein the processor is further configured to perform one or more of:

select neighbor nodes that are more likely to be strongly associated with each other;

select neighbor nodes that, based on aggregate user activity history, have a higher likelihood to be associated; and

determine which neighbor concepts in the concept map are tied to a form of monetization that yields a highest conversion rate.

18. The apparatus of claim 11 , wherein the apparatus is further configured to map one or more advertisements to the web page based at least in part on the expanded set of concepts.