Method for analyzing and classifying electronic document

• US 20060085405A1
• Filed: 02/02/2005
• Published: 04/20/2006
• Est. Priority Date: 10/18/2004
• Status: Abandoned Application

• Current Assignee: Avectec Com Incorporated
• Original Assignee: Avectec Com Incorporated
• Inventors: Ho, Pei-Hsun, Hou, Jiang-Liang, Trappey, Amy J.C., Liu, Shang-Jyh, Trappey, Charles V., Hsu, Fu-Chiang
• Application Number:
  US11/049,792
• Publication Number:
  US 20060085405A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/93 Document management systems

Abstract

A method for analyzing and classifying electronic documents. The method comprises steps of fetching an electronic document from an electronic document folder, wherein the electronic document comprises a plurality of key words. Then, the key words are retrieved. Further, according to an appearance frequency of each key word, a correlation between each two key words is calculated. Further, according to the correlations between the key words, the key words are classified into at least one technology group. Finally, the documents in the document folder are classified into at least one document group.

Claims

1. A method for analyzing and classifying electronic documents, comprising:

fetching an electronic document from an electronic document folder, wherein the electronic document comprises a plurality of key words;

retrieving the key words;

calculating a correlation between each two key words according to an appearance frequency of each key word; and

classifying the key words into at least one technology group according to the correlations between the key words.

2. The method of claim 1, wherein the step of retrieving the key words include at least one step selected form a group composed of word section analyzing, rhetoric analyzing, vocabulary comparison, word frequency maintaining, retrieving the key word of the candidate word library and retrieving the key word of the word library waiting for confirmation.

3. The method of claim 1, wherein the step of calculating the correlation between each two key words according to the appearance frequency of each key word comprises steps of:

de-duplicating the identical key words with merging the appearance frequencies thereof; and

calculating the correlation of each two key words.

4. The method of claim 3, wherein the step of de-duplicating the identical key words with merging the appearance frequencies thereof comprises steps of:

retrieving the key words from the electronic document;

merging the duplicated key words; and

re-calculating the appearance frequencies of the key words.

5. The method of claim 3, wherein the step of re-calculating the correlation of each two key words comprises steps of:

obtaining the appearance frequency of each key word; and

calculating a correlation coefficient between each two key words, wherein the correlation coefficient between each two key word denotes the correlation between the appearance frequencies of the key words.

6. The method of claim 1, wherein the step of classifying the key words comprises steps of:

forming a vocabulary data by using the correlations and a Cartesian dimension system with a dimension corresponding to the number of the key words, wherein each key word is represented by a data point with a coordinate composed by the correlation coefficients; and

grouping the data points in the vocabulary data into at least one technology group by using K-Means algorithm.

7. The method of claim 1, further comprises a step of obtaining a maturity of a technology group by using the number of the key words, the number of the electronic documents in the technology group and the number of the key words in the technology group.

8. A method for analyzing and classifying electronic documents, comprising:

fetching a plurality of documents from a document folder, wherein at least one of the electronic documents includes at leas a technology group;

obtaining the technology groups in the electronic documents;

statically calculating an appearance frequency of each technology group in the electronic documents; and

classifying the electronic documents into at least one document group according to the appearance frequency of each technology group in the electronic documents.

9. The method of claim 8, wherein the step of obtaining the technology groups in the electronic documents comprises steps of:

retrieving a plurality of key words in the electronic documents;

calculating a correlation between each two key words according to an appearance frequency of each key word; and

classifying the key words into at least one technology group according to the correlations between the key words.

10. The method of claim 9, wherein the step of retrieving the key words include at least one step selected form a group composed of word section analyzing, rhetoric analyzing, vocabulary comparison, word frequency maintaining, retrieving the key word of the candidate word library and retrieving the key word of the word library waiting for confirmation.

11. The method of claim 9, wherein the step of calculating the correlation between each two key words according to the appearance frequency of each key word comprises steps of:

de-duplicating the identical key words with merging the appearance frequencies thereof; and

calculating the correlation of each two key words.

12. The method of claim 11, wherein the step of de-duplicating the identical key words with merging the appearance frequencies thereof comprises steps of:

retrieving the key words from the electronic documents;

merging the duplicated key words; and

re-calculating the appearance frequencies of the key words.

13. The method of claim 11, wherein the step of re-calculating the correlation of each two key words comprises steps of:

obtaining the appearance frequency of each key word; and

calculating a correlation coefficient between each two key words, wherein the correlation coefficient between each two key word denotes the correlation between the appearance frequencies of the key words.

14. The method of claim 9, wherein the step of classifying the key words comprises steps of:

forming a vocabulary data by using the correlations and a Cartesian dimension system with a dimension corresponding to the number of the key words, wherein each key word is represented by a data point with a coordinate composed by the correlation coefficients; and

grouping the data points in the vocabulary data into at least one technology group by using K-Means algorithm.

15. The method of claim 8, wherein the step of classifying the electronic documents comprises steps of:

forming a technology data by using the appearance frequency of each technology group and a Cartesian dimension system with a dimension corresponding to the number of the technology groups, wherein each technology group is represented by a data point with a coordinate composed by the appearance number of each technology group; and

grouping the data points in the technology data into at least one document group by using K-Means algorithm.