Systems and methods for identifying a named entity

• US 20080005090A1
• Filed: 03/31/2004
• Published: 01/03/2008
• Est. Priority Date: 03/31/2004
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Khan, Omar, Wang, Niniane, Lawrence, Stephen
• Granted Patent: US 9,009,153 B2
• Time in Patent Office: Days
• US Class Current: 707/4
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

Systems and methods for identifying a named entity are described. In one described system, a computer program, such as a query system, identifies an event associated with an article, identifies a named entity within the event, and creates an implicit search query comprising the named entity.

Claims

1. A method comprising:

identifying an event associated with an article;

identifying a plurality of named entities within the event;

determining a weight to associate with each of the plurality of named entities based at least in part on a frequency of each of the plurality of named entities within a data store; and

creating an implicit search query based at least in part on each of the plurality of named entities and the associated weight, the implicit search query focused on a named entity with a higher associated weight more than on a named entity with a lower associated weight.

2. The method of claim 1, further comprising determining a list of named entities.

3. The method of claim 2, wherein identifying a plurality of named entities within the event comprises identifying an entity in the event that matches an entity in the list of named entities.

4. The method of claim 2, wherein determining the list of named entities comprises monitoring instant messaging traffic.

5. The method of claim 2, wherein determining the list of named entities comprises analyzing an email data store.

6. The method of claim 2, wherein determining the list of named entities comprises analyzing a directory structure.

7. The method of claim 2, wherein determining the list of named entities comprises searching a contact list.

8. The method of claim 2, wherein determining the list of named entities comprises searching a news list.

9. The method of claim 2, wherein determining the list of named entities comprises part of speech tagging.

10. The method of claim 1, wherein the named entity comprises one of an email address, an instant messaging name, and a proper noun.

11. The method of claim 1, further comprising storing the named entity in a user profile.

12. The method of claim 1, further comprising identifying a plurality of named entities for a name by using first name only, last name only, and combinations thereof.

13. The method of claim 12, further comprising filtering out at least one of the plurality of named entities having a high document frequency (DF).

15. The method of claim 1, further comprising:

receiving a result set associated with the implicit search query; and

outputting the result set.

16. The method of claim 15, further comprising:

receiving an interest signal associated with one of the plurality of named entities; and

ranking the result set based at least in part on the interest signal.

37. The method of claim 1, wherein the frequency of each named entity comprises an inverse document frequency of that named entity within the data store.

38. The method of claim 1, wherein the frequency of each named entity comprises a term frequency of that named entity within the data store.

14. (canceled)

17. (canceled)

18. (canceled)

19. A method comprising:

receiving an event;

identifying a plurality of named entities in the event;

determining a weight to associate with each of the plurality of named entities based at least in part on a frequency of each of the plurality of named entities within a data store;

creating an implicit query based at least in part on each of the plurality of named entities and the associated weight, the implicit search query focused on a named entity with a higher associated weight more than on a named entity with a lower associated weight;

transmitting the implicit query to a search engine; and

receiving a result set from the search engine, the result set comprising one or more article identifiers; and

responsive to an associated score exceeding a threshold, outputting the one or more article identifiers.

20. A computer-readable medium on which is encoded program code, the program code comprising:

program code for identifying an event associated with an article;

program code for identifying a plurality of named entities within the event;

program code for determining a weight to associate with each of the plurality of named entities based at least in part on a frequency of each of the plurality of named entities within a data store; and

program code for creating an implicit search query based at least in part on each of the plurality of named entities and the associated weight, the implicit search query focused on a named entity with a higher associated weight more than on a named entity with a lower associated weight.

21. The computer-readable medium of claim 20, further comprising program code for determining a list of named entities.

22. The computer-readable medium of claim 20, wherein program code for identifying a plurality of named entities within the event comprises program code for identifying an entity in the event that matches an entity in the list of named entities.

23. The computer-readable medium of claim 20, further comprising program code for storing the named entity in a user profile.

24. The computer-readable medium of claim 21, wherein program code for determining the list of named entities comprises program code for monitoring instant messaging traffic.

25. The computer-readable medium of claim 21, wherein program code for determining the list of named entities comprises program code for analyzing an email data store.

26. The computer-readable medium of claim 21, wherein program code for determining the list of named entities comprises program code for analyzing a directory structure.

27. The computer-readable medium of claim 21, wherein program code for determining the list of named entities comprises program code for searching a contact list.

28. The computer-readable medium of claim 21, wherein program code for determining the list of named entities comprises program code for searching a news list.

29. The computer-readable medium of claim 21, wherein program code for determining the list of named entities comprises program code for part of speech tagging.

30. The computer-readable medium of claim 20, further comprising:

program code for receiving a result set associated with the implicit search query; and

program code for outputting the result set.

31. The computer-readable medium of claim 30, further comprising:

program code for receiving an interest signal associated with one of the plurality of named entities; and

program code for ranking the result set based at least in part on the interest signal.

32. The computer-readable medium of claim 31, further comprising program code for identifying a plurality of named entities for a name by using first name only, last name only, and combinations thereof.

33. The computer-readable medium of claim 31, further comprising program code for filtering out at least one of the plurality of named entities having a high document frequency (DF).

40. The computer-readable medium of claim 20, wherein the frequency of each named entity comprises an inverse document frequency of that named entity within the data store.

41. The computer-readable medium of claim 20, wherein the frequency of each named entity comprises a term frequency of that named entity within the data store.

34. (canceled)

35. (canceled)

36. A computer-readable medium on which is encoded program code, the program code comprising:

program code for receiving an event;

program code for identifying a plurality of named entities in the event;

program code for determining a weight to associate with each of the plurality of named entities based at least in part on a frequency of each of the plurality of named entities within a data store;

program code for creating an implicit query based at least in part on each of the plurality of named entities and the associated weight, the implicit search query focused on a named entity with a higher associated weight more than on a named entity with a lower associated weight;

program code for transmitting the implicit query to a search engine; and

program code for receiving a result set from the search engine, the result set comprising one or more article identifiers; and

responsive to an associated score exceeding a threshold level of relevance, outputting the one or more article identifiers.

39. (canceled)

42. (canceled)