Electronic document classification

• US 8,745,091 B2
• Filed: 05/18/2010
• Issued: 06/03/2014
• Est. Priority Date: 05/18/2010
• Status: Active Grant

• Current Assignee: Innovative Discovery, LLC
• Original Assignee: Integro, Inc.
• Inventors: McHenry, Christopher A., Burt, Scott W.
• Primary Examiner(s): Woo, Isaac M
• Application Number:
  US12/781,939
• Publication Number:
  US 20100332428A1
• Time in Patent Office: 1,477 Days
• Field of Search: 707600-899
• US Class Current: 707/791
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

An electronic document classification system disclosed herein classifies electronic documents. The classification of the documents may involve analyzing the document and the information attached to the document to generate a set of classification data and comparing the classification data with one or more classification rules to generate a set of classifying data. The system attaches the set of classifying data to the electronic document and displays the electronic document based on the set of classifying data. The classification data may also be used to prioritize the electronic documents and to assign a retention period to the electronic documents. The system is further adapted to receive user feedback regarding the classification of the electronic document and to update the classification rules.

Claims

1. In a computing system, a method comprising:

analyzing an electronic document to generate document identifying data;

classifying the electronic document in one of one or more display categories by applying a classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document;

displaying the classified electronic document in the one of the one or more display categories;

receiving a user feedback regarding prioritization of the one of the electronic document; and

updating the classification rule based on the feedback from the user,

wherein analyzing the electronic document further comprises analyzing the document using semantical analysis of the document comprising;

associating one or more concepts with the one of the one or more display categories,

extracting the one or more concepts from the electronic document, and

pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories.

2. The method of claim 1, wherein the user feedback is in the form of the user moving the electronic document from the one of the one or more display categories to the another of the one or more display categories.

3. The method of claim 1, wherein the user feedback is in the form of the user not reviewing the electronic document.

4. The method of claim 1, wherein the electronic document is an email and wherein displaying the classified electronic document further comprises displaying the classified electronic document in an email inbox of the user.

5. The method of claim 1, wherein the user feedback is an override of the classification based on the classification rule.

6. The method of claim 1, further comprising updating the classification rule in response to the user override feedback.

7. The method of claim 1, further comprising updating the classification rule based on analysis of electronic documents by an end user.

8. The method of claim 1, wherein classifying the electronic document further comprises:

using semantic analysis to provide suggestive classification for the electronic document; and

allowing the user to select one of the suggestive classification,

wherein updating the classification rule further comprises updating the classification rule based on the selection of the suggestive classification.

9. The method of claim 1, wherein analyzing the electronic document includes analyzing at least one of (i) an electronic document recipient'"'"'s address, (ii) metadata attached to the electronic document, (iii) a title of the electronic document, (iv) content attached to the electronic document, and (v) content of the electronic document.

10. The method of claim 1, further comprising prioritizing the electronic document based on the document identifying data.

11. The method of claim 1, further comprising prioritizing the electronic document based on the category of the document.

12. The method of claim 1, wherein the electronic document identifying data includes a confidence level representative of a priority level of the electronic document.

13. The method of claim 1, further comprising assigning a retention level to the electronic document based on the classification of the electronic document.

14. The method of claim 1, further comprising assigning an auto-deletion time to the electronic document based on the classification of the electronic document.

15. The method of claim 14, further comprising:

determining, on a periodic basis, if the electronic document is to be deleted and providing a message to a user if the electronic document is to be deleted.

16. The method of claim 15, further comprising developing the classification rule based on a community knowledge base, wherein the organization is related to the community.

17. The method of claim 1, further comprising modifying a classification rule based on a feedback of a recipient of the electronic document and a collective knowledge base of an organization, wherein the recipient is a member of the organization.

18. The method of claim 1, wherein classifying the electronic document further comprises classifying the electronic document one of (i) a potential corporate record category;

(ii) a classified document category; and

(iii) an optional reading category.

19. The method of claim 1, further comprising assigning workspace quota to each of the one or more categories.

20. The method of claim 1, wherein receiving an input from a user further comprises receiving a request to use the user selected classification to update a suggestive classification modeling engine.

21. The method of claim 20, wherein receiving an input from a user further comprises the user ignoring the electronic document.

22. A computer system comprising a computer program, said computer program stored in a memory and operable to cause a processor to:

analyze, using a computer processor, an electronic document to generate document identifying data;

classify the electronic document in one of one or more display categories by applying one of natural language processing and semantic analysis to the document identifying data to provide suggestive classification, wherein the classification of the electronic document represents a prioritization of the electronic document;

display the classified electronic document in the one of the one or more display categories;

receive a user feedback reclassifying the electronic document into another of the one or more display categories;

update the classification rule based on the feedback from the user; and

if the electronic document is classified in a first category;

store the electronic document in an archive and assign a first retention period to the electronic document, and

generate a convenience co of the electronic document and assign a second retention period to the convenience copy, wherein the second retention period is smaller than the first retention period.

23. The computer system of claim 22, wherein the user feedback is in the form of the user moving the electronic document from the one of the one or more display categories to the another of the one or more display categories.

24. The computer system of claim 23, wherein the electronic document is an email and wherein said computer program is further operable to cause the processor to display the classified electronic document in an email inbox of the user.

25. The computer system of claim 22, wherein said computer program is further operable to assign a retention level or an auto-deletion time to the electronic document based on the classification of the electronic document.

26. The computer system of claim 25, wherein said computer program is further operable to determine whether the electronic document is to be deleted based on the retention level or the auto-deletion time assigned to the electronic document.

27. The computer system of claim 22, wherein the one or more categories comprises (i) a high importance document category;

(ii) a low importance category; and

(iii) optional reading documents category.

28. The computer system of claim 22, wherein said computer program is further operable to assign a workplace quota to each of the one or more categories.

29. One or more non-transitory computer-readable storage media encoding computer-executable instructions for executing on a computer system a computer process for classifying electronic documents, the computer process comprising:

analyzing an electronic document to generate document identifying data;

classifying the electronic document in one of one or more categories by applying a suggestive classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document;

receiving an input from a user reclassifying the electronic document into another of the one or more categories, wherein the user feedback is in the form of the user moving the electronic document from the one of the one or more categories to the another of the one or more categories;

updating the classification rule based on the input from a user

assigning an auto-deletion period to the electronic document based on the document identifying data; and

deleting the electronic document if the auto-deletion period has expired.

30. The computer-readable storage media of claim 29, wherein said computer process further comprising displaying the classified electronic document in the one or more categories.

31. The computer-readable storage media of claim 29, wherein said analyzing the electronic document further comprises analyzing metadata attached to the electronic document.

32. The computer-readable storage media of claim 29, wherein classifying the electronic document further comprising:

associating a series of concepts to the electronic documents; and

pattern matching the concepts associated with the electronic documents with concepts identified in a knowledge base.

33. A user interface for a computer monitor, comprising:

a display of a first listing of electronic documents;

the first listing of electronic documents comprising the electronic documents grouped under a plurality of categories, wherein the electronic documents are assigned to the plurality of categories by (i) analyzing, using a processor, the electronic document to generate document identifying data for each of the electronic documents;

(ii) classifying the electronic document in one of the one or more categories by applying a classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document;

(iii) receiving a user feedback requesting reclassification of the electronic document into another of the one or more categories, wherein the user feedback is an override of the classification based on the classification rule; and

(iv) updating the classification rule based on the user feedback;

wherein analyzing the electronic document further comprises analyzing the document using semantical analysis of the document comprising;

associating one or more concepts with the one of the one or more display categories;

extracting the one or more concepts from the electronic document; and

pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories.

34. The user interface if claim 33, wherein the one or more categories includes (i) a potential corporate record category;

(ii) a classified document category; and

(iii) an optional reading category.

35. The user interface of claim 33, further comprising:

a second listing of a workspace usage summary identifying (i) workspace quotas assigned to one of the one or more categories; and

(ii) workspace utilized for the one of the one or more categories.

36. The user interface of claim 33, further comprising:

a third listing of one or more options, wherein a user may select the one or more option to reclassify one of the electronic documents.

37. A method comprising:

providing computer software encoded on one or more computer-readable media, executable on a computer processor, and configured to;

suggestively classify an electronic document in one of one or more categories by applying a classification rule to a series of concepts associated with the electronic document, wherein the classification of the electronic document represents a prioritization of the electronic document;

display the classified electronic document in the one of the one or more categories;

receive a user feedback overriding the prioritization of the one of the electronic document;

update the classification rule in response to the user feedback;

wherein suggestively classifying the electronic document further comprises analyzing the document using semantical analysis of the document comprising;

associating one or more concepts with the one of the one or more display categories,

extracting the one or more concepts from the electronic document, and

pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories.

38. The method of claim 37, wherein the computer software is further configured to reclassify the electronic document using the updated classification rule.