Systems and methods for automatic emphasis of freeform annotations

• US 20030070139A1
• Filed: 09/16/2002
• Published: 04/10/2003
• Est. Priority Date: 09/14/2001
• Status: Active Grant

• Current Assignee: Fuji Xerox Company Limited (Xerox Holdings Corp.)
• Original Assignee: Fuji Xerox Company Limited (Xerox Holdings Corp.)
• Inventors: Tanaka, Kei, Golovchinsky, Gene, Marshall, Catherine C., Schilit, William N., Shipman, Frank M. III, Price, Morgan N.
• Granted Patent: US 6,900,819 B2
• Time in Patent Office: Days
• US Class Current: 715/512
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06F 40/171 by use of digital ink

Abstract

A system for automatic emphasis of freeform annotations contained within an electronic document is performed based on a determined importance of each annotation. The importance of each annotation is determined by a mark parser that groups, types and ranks each of the annotations. A weighted value is assigned to each grouped, ranked and typed annotation based on temporal and spatial information. The display characteristics of the weighted annotation is altered based on the weighted value.

Claims

1. A method for emphasizing freeform annotations, comprising:

inputting received document data;

inputting at least one freeform annotation in the received document data;

determining from the at least one freeform annotation a reader annotation style;

determining an importance of at least one of the at least one freeform annotation based on the determined reader annotation style; and

outputting a reduced representation of at least a portion of the received document data and outputting a representation of at least one freeform annotation, the outputting of the representation of the at least one freeform annotation being based on the determined importance of that at least one freeform annotation.

2. The method of claim 1, further comprising assigning for each of at least one of the at least one freeform annotation a weighted value to that freeform annotation based on the determined importance of that freeform annotation.

3. The method of claim 1, further comprising, for each of at least one of the at least one freeform annotation, altering the output of that freeform annotation based on a weighted value associated with that freeform annotation.

4. The method of claim 3, further comprising treating a freeform annotation having a greater weight as a higher valued freeform annotation.

5. The method of claim 3, wherein altering the output comprises altering at least one of font size, font color, underlining, highlighting and iconization.

6. The method of claim 1, wherein inputting at least one freeform annotation comprises extracting characteristic information about at least one of the at least one freeform annotation, the characteristic information including at least one of at least a time stamp indicating when a freeform annotation was made, a physical size measurement of a freeform annotation and a type of device used to make a freeform annotation.

7. The method of claim 6, wherein determining from the at least one freeform annotation a reader annotation style comprises grouping a plurality of the at least one freeform annotation into at least one group of freeform annotations based on the extracted characteristic information.

8. The method of claim 7, wherein determining the importance of at least one of the at least one freeform annotation comprises:

grouping a plurality of groups of freeform annotations into at least one level of higher level groups; and

ranking and typing a relative importance of the plurality of groups.

9. The method of claim 1, wherein determining the importance comprises determining a frequency of occurrence of a particular type of each of at least one freeform annotation associated with the document data.

10. The method of claim 9, wherein determining the importance further includes:

clustering a plurality of the at least one freeform annotations into one-level or multi-level hierarchical groups;

categorizing the clustered plurality of freeform annotations into freeform annotation types; and

grouping the categorized and clustered plurality of freeform annotations with passages from the document data, wherein an overlap between the grouped passages produce a multi-mark cluster.

11. The method of claim 10, further comprising assigning, for each of at least one of the at least one freeform annotation, a weighted value to each of the clustered, categorized and grouped freeform annotations.

12. The method of claim 11, wherein outputting a reduced representation further includes altering the output of the at least one freeform annotation based on the assigned weighted value.

13. A freeform annotation emphasis system that emphasizes high-value freeform annotations, comprising:

a freeform annotation detection circuit or routine that detects and identifies at least one freeform annotation within electronic document data supplied from an electronic data source;

an emphasis determination circuit or routine that ranks and types the relative importance of each of the at least one freeform annotations; and

a freeform annotation altering circuit or routine that alters an output of at least one freeform annotation based on the determined importance of the at least one freeform annotation.

14. The system of claim 13, wherein the emphasis determination system comprises:

a frequency counter that determines a frequency of occurrence of a freeform annotation type within the document data;

a cluster circuit that produces one-level or multi-level hierarchical clustering of each of the at least one freeform annotations into groups; and

a mark parser that types, ranks and groups each of the at least one freeform annotations, wherein the mark parser assigns a weighted value to the typed, ranked and grouped freeform annotations to indicate importance.

15. The system of claim 14, wherein upon detecting and identifying a freeform annotation, the freeform annotation detection circuit or routine captures freeform annotation information.

16. The system of claim 15, wherein the captured freeform annotation includes at least one of a time stamp indicating when a freeform annotation was made, a physical size of a freeform annotation and a type of device used to make the freeform annotation.

17. The system of claim 14, wherein the mark parser uses the frequency of occurrence information from the frequency counter to characterize a reader annotation style.

18. The system of claim 17, wherein the mark parser uses the frequency of occurrence information to determine the relative importance of a freeform annotation, with the freeform annotation having the highest frequency of occurrence being marked as the high-value freeform annotation.

19. The system of claim 17, wherein the mark parser ranks, types and groups the freeform annotations by:

clustering a plurality of the at least one freeform annotation into one level or multi-level hierarchical groups;

categorizing the clustered plurality of freeform annotations into freeform annotation types; and

grouping the categorized and clustered plurality of freeform annotations with passages from the document data, wherein an overlap between a pair of the grouped passages produce a multi-mark cluster.

20. The system of claim 19, wherein a weighted value is assigned to each group.

21. The system of claim 14, wherein the freeform annotation altering circuit or routine changes at least one output characteristic of the freeform annotation according to the assigned weighted value of the typed, ranked and grouped freeform annotation.

22. The system of claim 21, wherein the at least one output characteristic includes changing at least the font color, font size or adding an icon.