Systems and methods for classifying electronic documents

• US 9,298,814 B2
• Filed: 03/15/2013
• Issued: 03/29/2016
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Tsg Technologies, LLC
• Original Assignee: Maritz Holdings Inc. (InMoment, Inc.)
• Inventors: Bryars, Michael Wayne, Lu, Caimei, Prosser, Ricky John
• Primary Examiner(s): NGUYEN, CAM LINH T
• Application Number:
  US13/839,817
• Publication Number:
  US 20140280166A1
• Time in Patent Office: 1,110 Days
• Field of Search: 707/738, 707/737
• US Class Current: 1/1
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

A method of classifying an electronic document from an electronic media source includes generating statistical data from one or more training documents and creating a plurality of classification rules, including creating at least one topic model-based classification rule using the statistical data and creating at least one query-based classification rule using one or more user defined categories and the statistical data. The method further includes classifying the electronic document using the at least one topic model-based classification rule. Example systems for classifying an electronic document from an electronic media source are also disclosed.

Claims

1. A non-transitory computer readable medium storing computer-executable instructions for creating a plurality of classification rules to classify an electronic document from an electronic media source, the instructions including generating statistical data from one or more training documents, and creating a plurality of classification rules, including creating at least one topic model-based classification rule using the statistical data and creating at least one query-based classification rule using one or more user defined categories and the statistical data.

2. The non-transitory computer readable medium of claim 1 wherein the instructions include classifying the electronic document using the at least one topic model-based classification rule.

3. The non-transitory computer readable medium of claim 2 wherein classifying includes classifying the electronic document using the at least one topic model-based classification rule and the at least one query-based classification rule.

4. The non-transitory computer readable medium of claim 2 wherein classifying includes classifying the electronic document only using the at least one topic model-based classification rule.

5. The non-transitory computer readable medium of claim 2 wherein the statistical data includes a topic-term matrix having one or more topical categories and wherein classifying includes assigning at least one of the one or more topical categories of the topic-term matrix to the electronic document using the at least one topic model-based classification rule.

6. The non-transitory computer readable medium of claim 5 wherein the instructions include outputting the assigned at least one topical category of the electronic document.

7. The non-transitory computer readable medium of claim 5 wherein the instructions include selecting a query-based classification rule of the at least one query-based classification rule based on the assigned at least one topical category and wherein classifying includes categorizing the electronic document into at least one user defined category of the one or more user defined categories using the selected query-based classification rule.

8. The non-transitory computer readable medium of claim 7 wherein the instructions include outputting the at least one user defined category of the one or more user defined categories.

9. A computer system for classifying an electronic document from an electronic media source, the computer system comprising a communication network and a computer server in communication with the communication network, the computer server configured to receive the electronic document via the communication network, the computer server having memory and a processor, said memory including one or more training documents and one or more user defined categories, the processor configured to

generate statistical data from the one or more training documents,

create a plurality of classification rules, the classification rules including at least one topic model-based classification rule created using the statistical data and at least one query-based classification rule created using the one or more user defined categories and the statistical data, and

classify the electronic document using the at least one topic model-based classification rule.

10. The computer system of claim 9 wherein the one or more training documents include one or more unlabeled training documents.

11. The computer system of claim 9 wherein said memory further includes a test document and wherein the processor is configured to evaluate a classification rule of the classification rules on the test document to ensure the classification rule meets a defined threshold.

12. The computer system of claim 11 wherein the processor is configured to modify the classification rule if the classification rule is below the defined threshold.

13. The computer system of claim 12 wherein the processor is configured to modify the plurality of classification rules after a period of time.

14. The computer system of claim 13 wherein the statistical data includes a topic-term matrix and a document-topic matrix.

15. The computer system of claim 14 wherein the topic-term matrix includes one or more topical categories and wherein the processor is configured to classify the electronic document by assigning at least one of the one or more topical categories to the electronic document using the at least one topic model-based classification rule.

16. The computer system of claim 15 wherein the processor is configured to select a query-based classification rule of the at least one query-based classification rule using the assigned at least one topical category and wherein the processor is configured to classify the electronic document by categorizing the electronic document into at least one user defined category of the one or more user defined categories using the selected query-based classification rule.

17. The computer system of claim 9 wherein the processor is configured to modify the plurality of classification rules after a period of time.

18. The computer system of claim 9 wherein the statistical data includes a topic-term matrix and a document-topic matrix.

19. The computer system of claim 18 wherein the processor is configured to create the at least one query-based classification rule using the topic-term matrix.

20. The computer system of claim 18 wherein the topic-term matrix includes one or more topical categories and wherein the processor is configured to classify the electronic document by assigning at least one of the one or more topical categories to the electronic document using the at least one topic model-based classification rule.

21. The computer system of claim 20 wherein the processor is configured to output the assigned at least one topical category of the electronic document.

22. The computer system of claim 20 wherein the processor is configured to select a query-based classification rule of the at least one query-based classification rule using the assigned at least one topical category and wherein the processor is configured to classify the electronic document by categorizing the electronic document into at least one user defined category of the one or more user defined categories using the selected query-based classification rule.

23. The computer system of claim 22 wherein the processor is configured to output the at least one user defined category of the one or more user defined categories.