Computer-based system and method for generating, classifying, searching, and analyzing standardized text templates and deviations from standardized text templates

1. A computer system configured to automatically analyze text documents by performing the following steps:

comparing text from a subject text to text of a plurality of given text templates, each text template containing at least one paragraph of text;

determining which given text template or text templates has text that matches the text from the subject text document to a given degree of correspondence;

generating a report of the differences between the text from the subject text document and the text of the matching text template or text templates;

comparing a family of specimen text documents;

identifying one paragraph of text within one of the family of specimen text documents that most closely matches a paragraph of text in all of the other specimen text documents, as compared to all of the other paragraphs in the one specimen text document; and

generating one of the text templates containing at least the one identified paragraph of text.

2. The computer system of claim 1 wherein the identifying the paragraph that most closely matches step uses an edit distance algorithm.

3. The computer system of claim 1 wherein the identifying the paragraph that most closely matches step uses a longest common subsequence algorithm.

4. The computer system of claim 1 wherein the determining matches to a degree of correspondence step uses an edit distance algorithm.

5. The computer system of claim 1 wherein the determining matches to a degree of correspondence step uses a longest common subsequence algorithm.

6. The computer system of claim 1 wherein the differences in the report are computed according to an edit distance algorithm.

7. Non-transitory, tangible, computer readable media containing computer programming instructions that, when loaded in a computer system having a memory, cause the computer system, in response to user commands, to automatically analyze text documents by performing the following steps:

comparing text from a subject text document to text of a plurality of given text templates, each text template containing at least one paragraph of text;

determining which given text template or text templates has text that matches the text from the subject text document to a given degree of correspondence;

generating a report of the differences between the text from the subject text document and the text of the matching text template or text templates;

comparing a family of specimen text documents;

identifying one paragraph of text within one of the family of specimen text documents that most closely matches a paragraph of text in all of the other specimen text documents, as compared to all of the other paragraphs in the one specimen text document; and

generating one of the text templates containing at least the one identified paragraph of text.

8. The media of claim 7 wherein the identifying the paragraph that most closely matches step uses an edit distance algorithm.

9. The media of claim 7 wherein the identifying the paragraph that most closely matches step uses a longest common subsequence algorithm.

10. The media of claim 7 wherein the determining matches to a degree of Correspondence step uses an edit distance algorithm.

11. The media of claim 7 wherein the determining matches to a degree of correspondence step uses a longest common subsequence algorithm.

12. The media of claim 7 wherein the differences in the report are computed according to an edit distance algorithm.

13. A computer-implemented method of automatically analyzing text documents in which a computer performs the following steps:

comparing text from a subject text to text of a plurality of given text templates, each text template containing at least one paragraph of text;

determining which given text template or text templates has text that matches the text from the subject text document to a given degree of correspondence;

generating a report of the differences between the text from the subject text document and the text of the matching text template or text templates;

comparing a family of specimen text documents;

identifying one paragraph of text within one of the family of specimen text documents that most closely matches a paragraph of text in all of the other specimen text documents, as compared to all of the other paragraphs in the one specimen text document; and

generating one of the text templates containing at least the one identified paragraph of text.

14. The computer-implemented method of claim 13 wherein the identifying the paragraph that most closely matches step uses an edit distance algorithm.

15. The computer-implemented method of claim 13 wherein the identifying the paragraph that most closely matches step uses a longest common subsequence algorithm.

16. The computer-implemented method of claim 13 wherein the determining matches to a degree of correspondence step uses an edit distance algorithm.

17. The computer-implemented method of claim 13 wherein the determining matches to a degree of correspondence step uses a longest common subsequence algorithm.

18. The computer-implemented method of claim 13 wherein the differences in the report are computed according to an edit distance algorithm.