Disambiguation and Tagging of Entities

• US 20100293195A1
• Filed: 05/12/2009
• Published: 11/18/2010
• Est. Priority Date: 05/12/2009
• Status: Active Grant

• Current Assignee: Comcast Interactive Media LLC (Comcast Corporation)
• Original Assignee: Comcast Interactive Media LLC (Comcast Corporation)
• Inventors: Houghton, David F.
• Granted Patent: US 8,533,223 B2
• Time in Patent Office: Days
• US Class Current: 707/776
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06F 40/289 Phrasal analysis, e.g. finite state techniques or chunking
• CPC Class Codes: G06F 40/295 Named entity recognition
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

Tagging of content items and entities identified therein may include a matching process, a classification process and a disambiguation process. Matching may include the identification of potential matching candidate entities in a content item whereas the classification process may categorize or group identified candidate entities according to known entities to which they are likely a match. In some instances, a candidate entity may be categorized with multiple known entities. Accordingly, a disambiguation process may be used to reduce the potential matches to a single known entity. In one example, the disambiguation process may include ranking potentially matching known entities according to a hierarchy of criteria.

Claims

1. A method comprising:

identifying, at a processor, a candidate entity in a content item, wherein the candidate entity is a potential match with a first known entity identified in a memory;

performing a first categorization of the candidate entity based on a first set of factors, wherein the first categorization generates one or more decisions regarding at least one other candidate entity following the candidate entity in the content item;

performing a second categorization of the candidate entity, after the first categorization, based on a second set of factors, wherein the second set of factors is different from the first set of factors and includes the one or more decisions regarding the at least one other candidate entity;

determining, after the second categorization, that the candidate entity is categorized with a plurality of known entities;

in response to determining that the candidate entity is categorized with the plurality of known entities, disambiguating the candidate entity; and

tagging the candidate entity based on the disambiguation.

2. The method of claim 1, wherein the content item includes a plurality of text and wherein the candidate entity corresponds to at least one word in the plurality of text.

3. The method of claim 2, wherein identifying the candidate entity in the content item is performed using string matching.

4. The method of claim 1, wherein the candidate entity includes at least one of:

a person'"'"'s name and a title of a content item.

5. The method of claim 1, wherein the first set of factors includes a rate of co-occurrence between the candidate entity and the at least one other candidate entity.

6. The method of claim 1, wherein tagging the candidate entity includes assigning, in the memory, a database identifier of one of the plurality of known entities to the candidate entity.

7. The method of claim 1, wherein the first set of factors includes a word that immediately follows the candidate entity in the content item.

8. The method of claim 1, wherein the plurality of known entities includes the first known entity and a second known entity and wherein disambiguating the candidate entity includes:

ranking the first known entity and the second known entity based on a first match reliability criterion;

determining that the first known entity is ranked lower than the second known entity; and

removing the first known entity as a potential match with the candidate entity.

9. The method of claim 8, wherein the plurality of known entities includes a third known entity and wherein disambiguating the candidate entity further includes:

ranking the third known entity and the second known entity based on a second match reliability criterion;

determining that the third known entity is ranked lower than the second known entity based on the second match reliability criterion; and

removing the third known entity as a potential match with the candidate entity.

10. The method of claim 8, wherein the first match reliability criterion includes a number of candidate entities in the content item categorized as potential matches.

11. The method of claim 8, wherein the first match reliability criterion includes a match confidence.

12. The method of claim 8, wherein the first match reliability criterion includes a co-occurrence rate between the candidate entity and another candidate entity that is matched to only one known entity.

13. The method of claim 1, further comprising associating the tagged candidate entity with a link to additional information about the candidate entity.

14. A method comprising:

identifying, at a processor, a candidate entity in a content item, wherein the candidate entity is a potential match with a first known entity identified in a memory;

categorizing the candidate entity based on one or more decisions made regarding at least one other candidate entity preceding the candidate entity in the content item;

determining that the candidate entity is categorized with a plurality of known entities including the first known entity and a second known entity;

ranking the first known entity and the second known entity based on a first match reliability criterion;

determining that the first known entity is ranked lower than the second known entity; and

removing the first known entity as a potential match with the candidate entity.

15. The method of claim 14, wherein the plurality of known entities includes a third known entity and wherein the method further includes:

ranking the third known entity and the second known entity based on a second match reliability criterion;

determining that the third known entity is ranked lower than the second known entity based on the second match reliability criterion; and

removing the third known entity as a potential match with the candidate entity.

16. The method of claim 14, further comprising:

tagging the candidate entity with a database identifier of the second known entity; and

associating the tagged candidate entity with a link to additional information about the second known entity.

17. The method of claim 14, wherein the first match criterion includes a co-occurrence rate of the candidate entity with another candidate entity in the content item matched with only one known entity.

18. The method of claim 14, wherein the candidate entity is identified in the content item using string matching.

19. An apparatus comprising:

a processor; and

memory storing computer readable instructions that, when executed, cause the apparatus to;

identify a candidate entity in a content item, wherein the candidate entity is a potential match with a first known entity identified in the memory;

perform a first categorization of the candidate entity based on a first set of factors, wherein the first categorization generates one or more decisions regarding at least one other candidate entity following the candidate entity in the content item;

perform a second categorization of the candidate entity, after the first categorization, based on a second set of factors, wherein the second set of factors is different from the first set of factors and includes the one or more decisions regarding the at least one other candidate entity;

determine, after the second categorization, that the candidate entity is categorized with a plurality of known entities;

in response to determining that the candidate entity is categorized with the plurality of known entities, disambiguate the candidate entity; and

tag the candidate entity based on the disambiguation.

20. The apparatus of claim 19, wherein the apparatus includes a head-end of a media distribution system.

21. The apparatus of claim 19, wherein the apparatus includes a set top box.

22. The apparatus of claim 19, wherein tagging the candidate entity includes assigning, in the memory, a database identifier of one of the plurality of known entities to the candidate entity.

23. The apparatus of claim 19, wherein the first set of factors includes a word that immediately follows the candidate entity in the content item.

24. The apparatus of claim 19, wherein the plurality of known entities includes the first known entity and a second known entity and wherein disambiguating the candidate entity includes:

ranking the first known entity and the second known entity based on a first match reliability criterion;

determining that the first known entity is ranked lower than the second known entity; and

removing the first known entity as a potential match with the candidate entity.

25. An apparatus comprising:

a processor; and

memory storing computer readable instructions that, when executed, cause the apparatus to;

identify a candidate entity in a content item, wherein the candidate entity is a potential match with a first known entity identified in the memory;

categorize the candidate entity based on one or more decisions made regarding at least one other candidate entity preceding the candidate entity in the content item;

determine that the candidate entity is categorized with a plurality of known entities including the first known entity and a second known entity;

rank the first known entity and the second known entity based on a first match reliability criterion;

determine that the first known entity is ranked lower than the second known entity; and

remove the first known entity as a potential match with the candidate entity.

26. The apparatus of claim 25, wherein the apparatus includes a head-end of a media distribution system.

27. The apparatus of claim 25, wherein the apparatus includes a set top box.

28. The apparatus of claim 25, wherein the first match criterion includes a co-occurrence rate of the candidate entity with another candidate entity in the content item matched with only one known entity.

29. The apparatus of claim 25, wherein the candidate entity is identified in the content item using string matching.

30. One or more computer readable media storing computer readable instructions that, when executed, cause an apparatus to:

identify, at the apparatus, a candidate entity in a content item, wherein the candidate entity is a potential match with a first known entity identified in a memory;

perform a first categorization of the candidate entity based on a first set of factors, wherein the first categorization generates one or more decisions regarding at least one other candidate entity following the candidate entity in the content item;

perform a second categorization of the candidate entity, after the first categorization, based on a second set of factors, wherein the second set of factors is different from the first set of factors and includes the one or more decisions regarding the at least one other candidate entity;

determine, after the second categorization, that the candidate entity is categorized with a plurality of known entities;

in response to determining that the candidate entity is categorized with the plurality of known entities, disambiguate the candidate entity; and

tag the candidate entity based on the disambiguation.

31. The one or more computer readable media of claim 30, wherein the first set of factors includes a word that immediately follows the candidate entity in the content item.

32. The one or more computer readable media of claim 30, wherein the plurality of known entities includes the first known entity and a second known entity and wherein disambiguating the candidate entity includes:

ranking the first known entity and the second known entity based on a first match reliability criterion;

determining that the first known entity is ranked lower than the second known entity; and

removing the first known entity as a potential match with the candidate entity.

33. One or more computer readable media storing computer readable instructions that, when executed, cause an apparatus to:

identify a candidate entity in a content item, wherein the candidate entity is a potential match with a first known entity identified in the memory;

categorize the candidate entity based on one or more decisions made regarding at least one other candidate entity preceding the candidate entity in the content item;

determine that the candidate entity is categorized with a plurality of known entities including the first known entity and a second known entity;

rank the first known entity and the second known entity based on a first match reliability criterion;

determine that the first known entity is ranked lower than the second known entity; and

remove the first known entity as a potential match with the candidate entity.

34. The one or more computer readable media of claim 33, wherein the first match criterion includes a co-occurrence rate of the candidate entity with another candidate entity in the content item matched with only one known entity.

35. The one or more computer readable media of claim 33, wherein candidate entity is identified in the content item using string matching.