Merging of Multiple Data Sets

• US 20100169385A1
• Filed: 12/29/2008
• Published: 07/01/2010
• Est. Priority Date: 12/29/2008
• Status: Active Grant

• Current Assignee: Comcast Interactive Media LLC (Comcast Corporation)
• Original Assignee: Comcast Interactive Media LLC (Comcast Corporation)
• Inventors: Rubinoff, Robert
• Granted Patent: US 11,531,668 B2
• Time in Patent Office: Days
• US Class Current: 707/803
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/7867 using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings

Abstract

A method may comprise comparing a first data set with a second data set, the first data set associating a first plurality of names with a first plurality of roles, and the second data set associating a second plurality of names with a second plurality of roles. The method may further comprise generating a third data set based on an outcome of the comparing, such that the third data set associates a subset of the first plurality of names with a subset of the second plurality of roles. Apparatuses, methods, and software for performing these and other functions are also described.

Claims

1. A method, comprising:

comparing a first data set with a second data set, the first data set associating a first plurality of names with a first plurality of roles, and the second data set associating a second plurality of names with a second plurality of roles; and

generating in a computer a third data set based on an outcome of the comparing, such that the third data set associates a subset of the first plurality of names with a subset of the second plurality of roles.

2. The method of claim 1, wherein the first and second pluralities of names comprise names of persons.

3. The method of claim 2, wherein the roles comprise roles in television shows.

4. The method of claim 1, wherein the associations between the first plurality of names and the first plurality of roles define a first plurality of relationships, the associations between the second plurality of names and the second plurality of roles define a second plurality of relationships, and comparing comprises comparing the first plurality of relationships with the second plurality of relationships.

5. The method of claim 1, wherein the associations between the first plurality of names and the first plurality of roles define a first plurality of relationships, the associations between the second plurality of names and the second plurality of roles define a second plurality of relationships, each of the first and second plurality of roles is a role in an event, and comparing comprises:

determining which of the events of the first data set correspond to one or more of the events of the second data set, and

determining whether the relationships associated with the determined corresponding events of the first data set correspond to the relationships associated with the determined corresponding events of the second data set.

6. The method of claim 5, wherein generating comprises generating the third data set such that, for each of the relationships of the first data set that are determined to correspond to at least one of the relationships of the second data set, the name for that relationship of the first data set is associated with the role for that relationship of the second data set.

7. The method of claim 5, wherein the events comprise television shows, the names comprise names of persons, and the roles comprise roles of the persons in the television shows.

8. A computer-readable medium storing computer-executable instructions for performing a method, the method comprising:

comparing a first data set with a second data set, the first data set associating a first plurality of names with a first plurality of roles, and the second data set associating a second plurality of names with a second plurality of roles; and

generating a third data set based on an outcome of the comparing, such that the third data set associates a subset of the first plurality of names with a subset of the second plurality of roles.

9. The computer-readable medium of claim 8, wherein the first and second pluralities of names comprise names of persons.

10. The computer-readable medium of claim 9, wherein the roles comprise roles in television shows.

11. The computer-readable medium of claim 8, wherein the associations between the first plurality of names and the first plurality of roles define a first plurality of relationships, the associations between the second plurality of names and the second plurality of roles define a second plurality of relationships, and comparing comprises comparing the first plurality of relationships with the second plurality of relationships.

12. The computer-readable medium of claim 8, wherein the associations between the first plurality of names and the first plurality of roles define a first plurality of relationships, the associations between the second plurality of names and the second plurality of roles define a second plurality of relationships, each of the first and second plurality of roles is a role in an event, and comparing comprises:

determining which of the events of the first data set correspond to which of the events of the second data set, and

determining whether the relationships associated with the determined corresponding events of the first data set correspond to the relationships associated with the determined corresponding events of the second data set.

13. The computer-readable medium of claim 12, wherein generating comprises generating the third data set such that, for each of the relationships of the first data set that are determined to correspond to at least one of the relationships of the second data set, the name for that relationship of the first data set is associated with the role for that relationship of the second data set.

14. The computer-readable medium of claim 12, wherein the events comprise television shows, the names comprise names of persons, and the roles comprise roles of the persons in the television shows.

15. A method, comprising:

receiving a first data set representing relationships between a first plurality of names with a first plurality of events, and associating the first plurality of names with a plurality of first identifiers;

receiving a second data set representing relationships between a second plurality of names with a second plurality of events, and associating the second plurality of names with a plurality of second identifiers;

for each of the plurality of first identifiers, associating a third identifier with the first identifier;

determining a subset of the relationships of the second data set, such that each of the relationships of the subset corresponds to at least one of the relationships of the first data set;

for each of the subset of relationships, associating the second identifier of the name that is part of that relationship of the second data set with the third identifier of the name in the at least one corresponding relationship of the first data set; and

generating in a computer a third data set representing the associations between the first and third identifiers and the associations between the second and third identifiers.

16. The method of claim 15, wherein the names comprise names of persons, and the events comprise television shows.

17. The method of claim 15, wherein generating comprises generating the third data set that identifies those of the second identifiers associated with a relationship correspondence that is a one-to-plural or plural-to-one correspondence between the relationships of the first data set and the relationships of the second data set.

18. The method of claim 15, further comprising, for each of the relationships of the second data set that do not correspond to any relationship of the first data set, associating a fourth identifier with the second identifier of the name that is part of that relationship of the second data set, wherein generating comprises generating the third data set to represent the associations between the second and fourth identifiers.

19. A computer-readable medium storing computer-executable instructions for performing a method, the method comprising:

receiving a first data set representing relationships between a first plurality of names with a first plurality of events, and associating the first plurality of names with a plurality of first identifiers;

receiving a second data set representing relationships between a second plurality of names with a second plurality of events, and associating the second plurality of names with a plurality of second identifiers;

for each of the plurality of first identifiers, associating a third identifier with the first identifier;

determining a subset of the relationships of the second data set, such that each of the relationships of the subset corresponds to at least one of the relationships of the first data set;

for each of the subset of relationships of the second data set, associating the second identifier of the name that is part of that relationship of the second data set with the third identifier of the name in the at least one corresponding relationship of the first data set; and

generating a third data set representing the associations between the first and third identifiers and the associations between the second and third identifiers.

20. The computer-readable medium of claim 19, wherein the names comprise names of persons, and the events comprise television shows.

21. The computer-readable medium of claim 19, wherein generating comprises generating the third data set to identify those of the second identifiers that are associated with a relationship correspondence that is a one-to-plural or plural-to-one correspondence between the relationships of the first data set and the relationships of the second data set.

22. The computer-readable medium of claim 19, wherein the method further comprises, for each of the relationships of the second data set that do not correspond to any relationship of the first data set, associating a fourth identifier with the second identifier of the name that is part of that relationship of the second data set, and wherein generating comprises generating the third data set to represent the associations between the second and fourth identifiers.

23. A method, comprising:

receiving a first data set representing relationships between a first plurality of names with a first plurality of events, associating the first plurality of names with a plurality of first identifiers;

receiving a second data set representing relationships between a second plurality of names with a second plurality of events;

for each of at least some of the relationships of the second data set, performing only one of the following depending upon the relationships of the first data set;

associating the relationship of the second data set with one of the first identifiers, or

associating the relationship of the second data set with a second identifier; and

generating in a computer a third data set representing the associations between the relationships of the second data set with the first and second identifiers.

24. The method of claim 23, wherein the third data set is part of the first data set.

25. The method of claim 23, wherein the names comprise names of persons and the events comprise television shows.

26. A computer-readable medium storing computer-executable instructions for performing a method, the method comprising:

receiving a first data set representing relationships between a first plurality of names with a first plurality of events, associating the first plurality of names with a plurality of first identifiers;

receiving a second data set representing relationships between a second plurality of names with a second plurality of events;

for each of at least some of the relationships of the second data set, performing only one of the following depending upon the relationships of the first data set;

associating the relationship of the second data set with one of the first identifiers, or

associating the relationship of the second data set with a second identifier; and

generating a third data set representing the associations between the relationships of the second data set with the first and second identifiers.

27. The computer-readable medium of claim 26, wherein the third data set is part of the first data set.

28. The computer-readable medium of claim 26, wherein the names comprise names of persons and the events comprise television shows.

29. An apparatus, comprising:

a computer-readable medium; and

a processor,

wherein the apparatus is configured to;

compare a first data set with a second data set, the first data set associating a first plurality of names with a first plurality of roles, and the second data set associating a second plurality of names with a second plurality of roles, and

generate in a computer a third data set based on an outcome of the comparing, such that the third data set associates a subset of the first plurality of names with a subset of the second plurality of roles.

30. The apparatus of claim 29, wherein the names comprise names of persons and the roles comprise roles in television shows.

31. The apparatus of claim 29, wherein the associations between the first plurality of names and the first plurality of roles define a first plurality of relationships, the associations between the second plurality of names and the second plurality of roles define a second plurality of relationships, and the apparatus is configured to compare the first plurality of relationships with the second plurality of relationships.

32. The apparatus of claim 29, wherein the associations between the first plurality of names and the first plurality of roles define a first plurality of relationships, the associations between the second plurality of names and the second plurality of roles define a second plurality of relationships, each of the first and second plurality of roles is a role in an event, and the apparatus is configured to:

determine which of the events of the first data set correspond to one or more of the events of the second data set; and

determine whether the relationships associated with the determined corresponding events of the first data set correspond to the relationships associated with the determined corresponding events of the second data set.