Knowledge acquisition nexus for facilitating concept capture and promoting time on task

• US 8,488,916 B2
• Filed: 07/20/2012
• Issued: 07/16/2013
• Est. Priority Date: 07/22/2011
• Status: Active Grant

• Current Assignee: David S. Terman
• Original Assignee: David S. Terman
• Inventors: Terman, David S
• Primary Examiner(s): ZARKA, DAVID PETER
• Application Number:
  US13/554,398
• Publication Number:
  US 20130021346A1
• Time in Patent Office: 361 Days
• Field of Search: 382/305
• US Class Current: 382/315
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G09B 5/08 providing for individual presentation of information to a plurality of student stations

Abstract

Described herein is an interactive digital software program and hardware that enables rapid acquisition of textual or audio subject matter, its conversion to editable text and immediate compression into a user understandable summary. The software program maximizes “time on task” while minimizing the time-consuming steps of “concept capture” and “compression”. The instant invention provides an accurate condensate of textual subject matter in a fraction of the time it would take to prepare such a document by manual note taking. In a single step, mobile devices such as cameras, camera phones, tablets, iPODs™, scanners and the like rapidly capture textual images convert them to OCR and to a user understandable summary in a fraction of the time it takes to process such a document by manual note taking. With more study time available for repetitious practice of the lesson, the user improves preparedness and performance on tests and presentations.

Claims

1. A single-action method to facilitate identification, condensation and capture of key concepts from subject matter of printed paper text, said single-action method comprising;

(a) obtaining still images directly of said printed paper text with one or more compact, handheld, mobile data input devices comprising a digital camera and computer system wherein said compact, handheld, mobile data input device is selected from a group consisting of tablets;

(b) stabilizing, rotating, deskewing, brightening and focusing said still images; and

(c) converting said stabilized, rotated and focused still images into digitized text using software operating on said mobile data input device;

(d) converting said digitized text into editable text form using optical character recognition software; and

(e) converting said editable text form into a machine readable summary using text summarization software;

wherein said text summarization software that computes similarity measurements in text or between text and text excerpts from said editable text form, generates text relation maps for said similarity measurements that exceed a threshold value, and uses said text relation maps as inputs for (i) a clustering process to identify text themes;

(ii) traversing texts selectively using individual text excerpts; and

(iii) extracting summary statements; and

wherein said steps (a) through (e) are performed upon a single-click from a user.

2. The single-action method of claim 1, wherein said text summarization software comprises programs that generate vector space diagrams, weighted terms, linguistic, probabilistic, neural and text cohesion analysis alone or in combinations of two or more to compute similarity measurements in text or between text and text excerpts from said editable text form, generates text relation maps for said similarity measurements that exceed a threshold value, and uses said text relation maps as inputs for (i) a clustering process to identify text themes;

(ii) traversing texts selectively using individual text excerpts; and

(iii) extracting summary statements; and

wherein said steps (a) through (e) are performed upon a single-click from a user.

3. The single-action method according to claim 1, wherein key subject matter from said editable text is selected and highlighted by user and converted into said machine readable summary using said text summarization software.

4. The single-action method of claim 1, wherein said text summarization software computes similarity measurements between said text and a user query, generates text relation maps for said similarity measurements that exceed a threshold value, and uses said text relation maps as inputs for (i) a clustering process to identify text themes;

(ii) traversing texts selectively using individual text excerpts; and

(iii) extracting summary statements.

5. The single-action method of claim 1, wherein said machine readable summary is converted into an format selected from the group comprising Roman, numbered, alphabetical or bullet-point outline.

6. The single-action method of claim 1, wherein double clicking of selected words or phrases in said machine summary of said printed paper text displays the selected words or phrases in their original sentences or paragraphs in said editable text of said printed paper text.

7. The single-action method of claim 1, wherein word volume of said machine readable summary may be compressed to said word volume of 10% to 90% of the default value.

8. The single-action method of claim 1, wherein said summarization software comprises programs that highlight designated subsections of printed paper text and convert said subsections into said machine readable summaries using said text summarization software.