Systems and methods for generating context specific terms

• US 9,842,165 B2
• Filed: 06/09/2014
• Issued: 12/12/2017
• Est. Priority Date: 10/12/2011
• Status: Active Grant

• Current Assignee: D2L Corporation
• Original Assignee: D2L Corporation
• Inventors: Pearson, Brian, Auger, Jeremy Jason
• Primary Examiner(s): Ly, Anh
• Application Number:
  US14/300,190
• Publication Number:
  US 20140289215A1
• Time in Patent Office: 1,282 Days
• Field of Search: 707749, 707737, 707736, 707750, 707767, 707758, 707780, 707781, 707757, 707705, 707783, 707706, 707E17005, 707E17017, 707E17064, 707E17071, 707E17084, 707E17041, 707E17042, 707E17126, 715257, 715259, 715261, 715255, 715256, 715260, 704 9, 704 10, 704251, 704E15022, 704E15023, 704E15024, 704E15026, 704245, 706205, 706217, 706225
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/3322 using system suggestions G06F16/3325 takes precedence
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

Various embodiments are described herein that generally relate to systems and methods for generating context specific terms and performing various actions based on the context specific terms. One example embodiment includes a computer-implemented method for generating context specific terms comprising obtaining a collection of terms from at least one electronic file associated with a given context; comparing the collection of terms with a collection of expected terms to generate candidate terms that are not in the collection of expected terms; determining a relevance for each of the candidate terms; and determining whether to add a given candidate term to a collection of context specific terms for the given context if the relevance for the given candidate term is above a threshold.

Claims

1. A method for generating context specific terms at a computing device, the computing device comprising at least one processor, the method comprising the at least one processor:

scanning one or more electronic files stored on one or more repositories associated with an application service, wherein the one or more objects are associated with a given context;

obtaining, based on the scan of the one or more electronic files, a collection of candidate terms from the one or more electronic files associated with the given context;

determining a relevance for each of the candidate terms;

determining whether to add a given candidate term to a collection of context specific terms for the given context if the relevance for the given candidate term is above a threshold; and

if it is determined that the given candidate term is to be added, adding the given candidate term to the collection of context specific terms for the given context, and storing the collection of context specific terms in a file associated with the application service.

2. The method of claim 1, wherein determining whether to add the given candidate term to the collection of context specific terms comprises ensuring that the given candidate term is a valid term.

3. The method of claim 1, wherein determining the relevance comprises ranking the candidate terms.

4. The method of claim 1, wherein determining the relevance comprises obtaining a weighted frequency for the candidate terms.

5. The method of claim 4, wherein the candidate terms that are more common are more heavily weighted than the candidate terms that are less common.

6. The method of claim 1, wherein the method further comprises determining a source of the at least one electronic file.

7. The method of claim 6, wherein the determining of the source of the at least one electronic file comprises:

determining the one or more contexts for which the given candidate term has a relevance above a preset threshold; and

associating the one or more electronic files with the source corresponding to the one or more contexts for which the given candidate term has a relevance above the preset threshold.

8. The method of claim 6, wherein the source is at least one of an educational course, an organizational group, and a user.

9. The method of claim 1, wherein the method further comprises using the collection of context specific terms in a spell-check application.

10. The method of claim 1, wherein the method further comprises associating the collection of context specific terms with at least one of an educational course, an organizational group and a user identifier.

11. The method of claim 1, wherein the method further comprises seeding a glossary based upon one or more of the context specific terms for the given context.

12. The method of claim 1, wherein the method further comprises providing one or more of the context specific terms to a search engine that searches for one or more electronic files that are related to the one or more context specific terms.

13. The method of claim 1, wherein the one or more electronic files comprise at least one of a webpage, a word processing document, a spreadsheet, a presentation document, a search index of organizational content, database content, discussion forum content, and an email.

14. The method of claim 1, wherein the method further comprises classifying a given context specific term based on an assigned technical level as determined from metadata structure associated with a search of public files.

15. The method of claim 1, wherein the method further comprises classifying a given context specific term based on a subject matter of located files that use the context specific term.

16. The method of claim 1, wherein determining whether to add the given candidate term to the collection of context specific terms for the given context comprises comparing the collection of candidate terms to a current collection of content specific terms for the given context.

26. A non-transitory computer-readable storage medium storing instructions that, when executed, cause at least one processor to perform the method of claim 1.

17. A computing device for generating context specific terms, wherein the computing device comprises:

one or more data storage devices comprising at least one electronic file, wherein the one or more data storage devices are associated with an application service; and

at least one processor in data communication with the data storage device, the at least one processor being adapted to scan one or more electronic files stored on the data storage device, wherein the one or more objects are associated with a given context, to obtain, based on the scan of the one or more electronic files, a collection of candidate terms from the one or more electronic files associated with the given context;

to determine a relevance for each of the candidate terms;

to determine whether to add a given candidate term to a collection of context specific terms for the given context if the frequency of occurrence for the given candidate term is above a threshold; and

if it is determined that the given candidate term is to be added, to add the given candidate term to the collection of context specific terms for the given context, and store the collection of context specific terms in a file associated with the application service.

18. The computing device of claim 17, wherein the at least one processor is further adapted to determine the relevance by ranking the candidate terms.

19. The computing device of claim 17, wherein the at least one processor is further adapted to determine the relevance by obtaining a weighted frequency for the candidate terms.

20. The computing device of claim 17, wherein the at least one processor is further adapted to determine a source of the at least one electronic file.

21. The computing device of claim 20, wherein the at least one processor is further adapted to determine the one or more contexts for which the given candidate term has a relevance above a preset threshold, and to associate the one or more electronic files with the source corresponding to the one or more contexts for which the given candidate term has a relevance above the preset threshold.

22. The computing device of claim 21, wherein the source is at least one of an educational course, an organizational group, and a user.

23. The computing device of claim 17, wherein the at least one processor is further adapted to use the collection of context specific terms in a spell-check application.

24. The computing device of claim 17, wherein the at least one processor is further adapted to seed a glossary based upon one or more of the context specific terms for the given context.

25. The computing device of claim 17, wherein the at least one processor is further adapted to classify a given context specific term based on a subject matter of located files that use the context specific term.