Software Tool for Creating Outlines and Mind Maps that Generates Subtopics Automatically

• US 20090119584A1
• Filed: 10/28/2008
• Published: 05/07/2009
• Est. Priority Date: 11/02/2007
• Status: Abandoned Application

• Current Assignee: Steve Herbst
• Original Assignee: Steve Herbst
• Inventors: Herbst, Steve
• Application Number:
  US12/259,500
• Publication Number:
  US 20090119584A1
• Time in Patent Office: Days
• US Class Current: 715/273
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 16/367 Ontology

Abstract

A system automatically generates a text outline or mind map by applying pattern-matching translation rules to topic text. The system may be used as an educational aid for writing and/or brainstorming, or to enhance structured and in-depth thinking in any industry. A user may choose a topic, such as by choosing one of several topics displayed by the system or by typing a topic. In response, the system may apply rules to the topic to identify one or more relevant subtopics. The system may display the subtopics to the user. The user may select one of the subtopics, in response to which the system may apply the same or different rules to the subtopic to identify one or more additional subtopics. This process may be repeated to any depth to create and explore an outline, mind map, or other representation of topics related to the original topic.

Claims

1. A computer-implemented method comprising:

(A) identifying an input text string representing a topic;

(B) determining whether the input text string matches a text pattern specified by a premise of a predetermined rule;

(C) if the input text string satisfies the text pattern, then identifying a plurality of output text strings specified by a conclusion of the predetermined rule.

2. The method of claim 1, further comprising:

(D) before (B), identifying a canonical text string by applying, to the input text string, a canonical transformation rule which maps a plurality of forms of sentences into a single canonical form.

3. The method of claim 1, wherein (C) comprises identifying a plurality of output text strings including at least some text from the input text string.

4. The method of claim 1, wherein (B) comprises, for each rule R of a plurality of predetermined rules:

(B1) identifying a text pattern specified by a premise of rule R;

(B2) determining whether the input text string matches the text pattern specified by the premise of rule R; and

wherein (C) comprises;

(C1) if the input text string satisfies the text pattern specified by the premise of rule R, then identifying a plurality of output text strings specified by a conclusion of rule R.

5. The method of claim 1, wherein (A) comprises:

(A1) identifying an input text string representing a topic; and

wherein (B) comprises;

(B1) determining whether the input text string matches a text pattern specified by a premise of a predetermined rule, the text pattern including at least one wildcard term, by examining a portion of the text pattern not including the at least one wildcard term.

6. The method of claim 1, wherein (A) comprises:

(A1) identifying an input English text string representing a topic.

7. The method of claim 1, wherein (B) comprises:

(B1) determining whether the input text string matches a text pattern specified by a premise of a predetermined specific rule.

8. The method of claim 1, wherein (B) comprises:

(B1) determining whether the input text string matches a text pattern specified by a premise of a predetermined general rule.

9. The method of claim 1, further comprising:

(D) outputting the plurality of output text strings.

10. The method of claim 9, wherein the outputted plurality of output strings are editable as part of an outline or mind map.

11. The method of claim 1, wherein (B) further comprises:

(B1) in addition to determining whether the input text string matches the text pattern specified by the premise of the predetermined rule, generating a context text string based on the input text string and storing the context text string in memory.

12. The method of claim 5, wherein (B1) comprises:

(B1A) identifying the at least one wildcard term by comparing non-wildcard portions of the text string and the text pattern and assigning an intervening portion of the text string to the at least one wildcard term.

13. The method of claim 12, wherein (B1) comprises:

(B1A) examining the at least one wildcard term in addition to the portion of the text pattern not including the at least one wildcard term in the determining whether the input text string matches the text pattern specified by the premise of the predetermined rule.

19. The method of claim 11, wherein (B) further comprises:

(B2) using the context text string stored in memory in determining whether the input text string matches the text pattern specified by the premise of the predetermined rule.

14. A computer-implemented method comprising:

(A) selecting, on a computerized display, an input text string representing a topic;

(B) identifying a canonical text string by applying, to the input text string, a canonical transformation rule which maps a plurality of forms of sentences into a single canonical form;

(C) for each rule R of a plurality of predetermined rules;

(C1) identifying a text pattern specified by a premise of rule R;

(C2) determining whether the identified canonical text string matches the text pattern specified by the premise of rule R;

(D) if the identified canonical text string satisfies the text pattern specified by the premise of rule R, then identifying a plurality of output text strings specified by a conclusion of rule R;

(E) outputting the plurality of output text strings on the computerized display.

15. The method of claim 14, wherein (D) comprises identifying a plurality of output text strings including at least some text from the input text string.

16. The method of claim 14, wherein the outputted plurality of output strings are editable as part of an outline or mind map.

17. The method of claim 14, wherein (A) comprises selecting, by at least one of typing, editing, and inserting, on a computerized display, an input text string representing a topic.

18. The method of claim 14, wherein (C2) further comprises:

(C2A) in addition to determining whether the canonical text string matches the text pattern specified by the premise of the rule R, determining if there exists at least one specific context text string in memory, and wherein (D) further comprises;

(D1) in addition to if the canonical text string satisfies the text pattern, if there exists the at least one specific context text string in memory, then identifying the plurality of output text strings specified by the conclusion of the rule R.

20. An apparatus comprising

means for identifying an input text string representing a topic;

means for determining whether the input text string matches a text pattern specified by a premise of a predetermined rule; and

means for identifying a plurality of output text strings specified by a conclusion of the predetermined rule if the input text string satisfies the text pattern, then.

21. An apparatus comprising:

means for selecting, on a computerized display, an input text string representing a topic;

means for identifying a canonical text string by applying, to the input text string, a canonical transformation rule which maps a plurality of forms of sentences into a single canonical form;

for each rule R of a plurality of predetermined rules;

means for identifying a text pattern specified by a premise of rule R;

means for determining whether the identified canonical text string matches the text pattern specified by the premise of rule R;

means for identifying a plurality of output text strings specified by a conclusion of rule R if the identified canonical text string satisfies the text pattern specified by the premise of rule R; and

means for outputting the plurality of output text strings on the computerized display.