METHOD AND SYSTEM FOR TRACKING AUTHORSHIP OF CONTENT IN DATA

• US 20090007267A1
• Filed: 06/29/2007
• Published: 01/01/2009
• Est. Priority Date: 06/29/2007
• Status: Active Grant

• Current Assignee: Walter Hoffmann
• Original Assignee: Walter Hoffmann
• Inventors: HOFFMANN, WALTER
• Granted Patent: US 7,849,399 B2
• Time in Patent Office: Days
• US Class Current: 726/22
• CPC Class Codes: G06Q 10/00 Administration; Management

Abstract

According to one aspect of the invention, iterative local alignment is employed to process two versions of a text and to identify novel contributions and their positions in the newer text version. In one embodiment, the new or target version of the text is aligned to the old or reference version of the text in an iterative process. The iterative process produces a local alignment of both text versions, which is optimal according to the selected parameters. In another embodiment, aligned substrings are removed from the texts and the iterative process is continued until no more aligned substrings can be obtained. In one example, authorship may be transferred from every aligned substring of the reference text version to the corresponding substring of the target text version. In another example, authorship for unaligned substrings of the target text version may be assigned to the author of the target text version. In one embodiment, unaligned substrings of the reference text version can be identified as deleted by the author of the target text version. In another embodiment, deleted substrings can be stored latently and can be considered in subsequent alignments. In another aspect of the invention, the method and system for tracking authorship of content in data may be employed in collaborative text editing systems or in word processing applications to identify and track the contributions of individual authors.

Claims

1. A method for tracking authorship of content in data, the method comprising the acts of:

aligning at least a portion of data from reference data with at least a portion of the data from target data;

storing any aligned data and authorship information;

repeating the acts of aligning at least a portion of the data and storing any aligned data until no significant alignment of the data is obtained; and

storing any unaligned data and authorship information.

2. The method of claim 1, wherein the act of repeating the act of aligning at least a portion of the data comprises excluding previous alignment from consideration during subsequent acts of aligning.

3. The method of claim 1, wherein the act of aligning at least a portion of the data further comprises an act of removing the aligned data that is identified.

4. The method of claim 3, wherein the act of aligning at least a portion of the data further comprises replacing the removed aligned data with control information.

5. The method of claim 1, wherein the act of aligning at least a portion of the data further comprises the acts of:

identifying substrings;

and aligning the substrings.

6. The method of claim 5, wherein the act of aligning at least a portion of the data further comprises the acts of:

assigning a weight to at least one of the substrings; and

considering the weight of the at least one of the substrings in identifying alignment.

7. The method of claim 5, wherein the method further comprises an act of verifying a possible alignment exceeds an expected alignment score.

8. The method of claim 5, wherein the act of identifying substrings in the data includes identifying substrings in the data based on at least one of a punctuation mark, blank, and symbol.

9. The method of claim 5, wherein the act of aligning the substrings includes considering gaps within the alignment.

10. The method of claim 5, wherein the act of aligning the substrings includes considering sentence borders when identifying alignment.

11. The method of claim 5, wherein the act of aligning the substrings further comprises an act of considering partial substrings for alignment.

12. The method of claim 1, wherein the act of storing any unaligned data and authorship information further comprises the acts of displaying any unaligned data from the reference document as deleted data and displaying any unaligned data of the target document as inserted data.

13. The method of claim 1, wherein the method for tracking authorship of content in data is used to track authorship through a plurality of edit cycles by a plurality of authors.

14. The method of claim 1, wherein the act of aligning at least a portion of the data includes employing an optimal local alignment algorithm.

15. The method of claim 14, wherein the optimal local alignment algorithm comprises an adaptation of the Smith-Waterman algorithm.

16. A computer-readable medium having computer-readable signals stored thereon that define instructions that, as a result of being executed by a processor instruct the processor to perform a method for tracking authorship of content in data, the method comprising the acts of:

aligning at least a portion of the data from reference data with at least a portion of the data from target data;

storing any aligned data and authorship information;

repeating the acts of aligning at least a portion of the data and storing any aligned data until no significant alignment of the data is obtained; and

storing any unaligned data with authorship information.

17. A system for tracking authorship of content in data, the system comprising a processor configured to perform a method for tracking authorship of content in data, the processor comprising:

an alignment component adapted to compare data from reference data with data from target data to identify alignment of at least a portion of the data, wherein the alignment component is further adapted to identify alignments iteratively until no significant alignments of the data is obtained; and

a storage component adapted to store aligned portions of data and authorship information, wherein the storage component is further adapted to store any unaligned portions of the data and authorship information.

18. The system of claim 17, wherein the alignment component is further adapted to exclude previous alignment from consideration during subsequent acts of aligning.

19. The system of claim 17, wherein the alignment component is further adapted to remove aligned data that is identified.

20. The system of claim 19, wherein the alignment component is further adapted to replace the removed aligned data with control information.

21. The system of claim 17, wherein the alignment component is further adapted to identify substrings and align the substrings.

22. The system of claim 21, wherein the alignment component is further adapted to assign a weight to at least one of the substrings and consider the weight of the at least one of the substrings in identifying alignment.

23. The system of claim 21, further comprising a verification component adapted to verify a possible alignment exceeds an expected alignment score.

24. The system of claim 21, wherein the alignment component is further adapted to identify substrings in the data based on at least one of a punctuation mark, blank, and symbol.

25. The system of claim 21, wherein the alignment component is further adapted to consider gaps within the alignment.

26. The system of claim 21, wherein the alignment component is further adapted to consider sentence borders when identifying alignment.

27. The system of claim 21, wherein the alignment component is further adapted to consider partial substrings for alignment.

28. The system of claim 17, further comprising a display component that in combination with the alignment component is adapted to display any unaligned data from the reference document as deleted data and display any unaligned data of the target document as inserted data.

29. The system of claim 17, wherein the system for tracking authorship of content in data is adapted to track authorship through a plurality of edit cycles by a plurality of authors.

30. The system of claim 17, wherein the alignment component is further adapted to employ an optimal local alignment algorithm.

31. The system of claim 30, wherein the optimal local alignment algorithm comprises an adaptation of the Smith-Waterman algorithm.