SYSTEMS AND METHODS FOR CLASSIFYING ELECTRONIC DOCUMENTS

• US 20140280166A1
• Filed: 03/15/2013
• Published: 09/18/2014
• 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
• Granted Patent: US 9,298,814 B2
• Time in Patent Office: Days
• US Class Current: 707/738
• 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 method of classifying an electronic document from an electronic media source, the method comprising:

generating statistical data from one or more training documents, 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, and

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

2. The method of claim 1 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.

3. The method of claim 1 further comprising filtering each training document prior to creating the classification rules.

4. The method of claim 1 wherein creating includes evaluating a classification rule of the classification rules on a test document to ensure the classification rule meets a defined threshold.

5. The method of claim 4 wherein creating includes modifying the classification rule if the classification rule is below the defined threshold.

6. The method of claim 1 wherein the statistical data includes a topic-term matrix and a document-topic matrix.

7. The method of claim 6 wherein the topic-term matrix includes 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.

8. The method of claim 7 further comprising outputting the assigned at least one topical category of the electronic document.

9. The method of claim 1 wherein classifying includes classifying the electronic document only using the at least one topic model-based classification rule.

10. The method of claim 6 wherein creating includes creating the at least one query-based classification rule using the topic-term matrix.

11. The method of claim 10 further comprising 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.

12. The method of claim 11 further comprising outputting the at least one user defined category of the one or more user defined categories.

13. The method of claim 1 further comprising modifying the plurality of classification rules after a period of time.

14. The method of claim 1 wherein the one or more training documents include one or more unlabeled training documents.

15. 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.

16. 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.

17. The computer system of claim 16 wherein the one or more training documents include one or more unlabeled training documents.

18. The computer system of claim 16 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.

19. The computer system of claim 18 wherein the processor is configured to modify the classification rule if the classification rule is below the defined threshold.

20. The computer system of claim 19 wherein the processor is configured to modify the plurality of classification rules after a period of time.

21. The computer system of claim 20 wherein the statistical data includes a topic-term matrix and a document-topic matrix

22. The computer system of claim 21 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.

23. The computer system of claim 22 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.

24. (canceled)