U.S. patent application number 11/288800 was filed with the patent office on 2006-04-13 for robust anchoring of annotations to content.
This patent application is currently assigned to Microsoft Corporation. Invention is credited to David M. Bargeron, Alice Jane Bernheim Brush, Anoop Gupta.
Application Number | 20060080598 11/288800 |
Document ID | / |
Family ID | 33132278 |
Filed Date | 2006-04-13 |
United States Patent
Application |
20060080598 |
Kind Code |
A1 |
Bargeron; David M. ; et
al. |
April 13, 2006 |
Robust anchoring of annotations to content
Abstract
Annotations are robustly anchored to content. The robust
anchoring allows annotations to be associated with the content
independently of the format used to store the content. The
annotations can be re-anchored to the content after the content has
been modified, including modifications to the format used to store
the content.
Inventors: |
Bargeron; David M.;
(Seattle, WA) ; Brush; Alice Jane Bernheim;
(Seattle, WA) ; Gupta; Anoop; (Woodinville,
WA) |
Correspondence
Address: |
PERKINS COIE LLP/MSFT
P. O. BOX 1247
SEATTLE
WA
98111-1247
US
|
Assignee: |
Microsoft Corporation
Redmond
WA
|
Family ID: |
33132278 |
Appl. No.: |
11/288800 |
Filed: |
November 29, 2005 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
09949028 |
Sep 7, 2001 |
|
|
|
11288800 |
Nov 29, 2005 |
|
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Current U.S.
Class: |
715/232 |
Current CPC
Class: |
G06F 40/169
20200101 |
Class at
Publication: |
715/512 ;
715/530 |
International
Class: |
G06F 17/24 20060101
G06F017/24 |
Claims
1-34. (canceled)
35. A method of determining a portion of modified content to which
an annotation corresponds, the method comprising: receiving
annotation anchoring information, wherein the annotation anchoring
information describes a portion of the content that the annotation
corresponded to prior to the portion being modified; identifying
keywords in the modified content; determining, for a region of the
content that potentially corresponds to the annotation, a score for
the region based at least in part on the location of the keywords
in the content; repeating the determining for a plurality of
identified keywords in the content; and selecting the region having
the best score as the portion of content to which the annotation
corresponds.
36. A method as recited in claim 35, further comprising selecting
the region having the best score as the portion of content to which
the annotation corresponds if the best score exceeds a lower bound,
and otherwise selecting no region as the portion of content to
which the annotation corresponds.
37. A method as recited in claim 35, further comprising selecting
the region having the best score as the portion of content to which
the annotation corresponds without user input if the best score
exceeds a threshold value, and otherwise obtaining user input prior
to selecting the region having the best score as the portion of
content to which the annotation corresponds.
38. A method as recited in claim 37, wherein the user input
comprises a user request for a best guess as to the region to which
the annotation corresponds.
39. A method as recited in claim 35, further comprising selecting
the region having the best score as the portion of content to which
the annotation corresponds and stopping the repeating if the best
score exceeds a threshold value.
40. A method as recited in claim 35, wherein the content and the
modified content are stored in two different formats.
41. A method as recited in claim 35, wherein selecting the region
having the best score comprises selecting the region having the
highest score.
42. A method as recited in claim 35, wherein determining the score
for the region comprises: identifying each keyword in the
annotation anchoring information; selecting one of the keywords in
the annotation anchoring information; locating the selected keyword
in the modified content; locating one or more additional keywords
that are both identified in the annotation anchoring information
and that are within a particular distance in the modified content
of the selected keyword; and increasing the score for each of the
one or more additional keywords.
43. A method as recited in claim 42, wherein the particular
distance comprises twice the length of the portion of the content
that the annotation corresponding to prior to the portion being
modified.
44. A method as recited in claim 35, wherein determining the score
for the region comprises: selecting a keyword from the annotation
anchoring information; identifying, from the annotation anchoring
information, one or more beginning point features for the portion
of the content; locating the selected keyword in the modified
content; locating a point of the modified content that precedes the
selected keyword and that matches the one or more beginning point
features; and determining whether to increase the score for the
region including the selected keyword and the located point based
at least in part on the distance between the located point and the
selected keyword.
45. A method as recited in claim 44, wherein determining whether to
increase the score for the region comprises determining to increase
the score for the region if the distance from the located point to
the selected keyword is not greater than a threshold amount.
46. A method as recited in claim 44, wherein the located point
comprises an intermediate point.
47. A method as recited in claim 35, wherein determining the score
for the region comprises: selecting a keyword from the annotation
anchoring information; identifying, from the annotation anchoring
information, one or more ending point features for the portion of
the content; locating the selected keyword in the modified content;
locating a point of the modified content that succeeds the selected
keyword and that matches the one or more ending point features; and
determining whether to increase the score for the region including
the selected keyword and the located point based at least in part
on the distance between the selected keyword and the located
point.
48. A method as recited in claim 47, wherein determining whether to
increase the score for the region comprises determining to increase
the score for the region if the distance from the selected keyword
to the located point is not greater than a threshold amount.
49. A method as recited in claim 47, wherein the located point
comprises an intermediate point.
50-56. (canceled)
57. One or more computer readable media having stored thereon a
plurality of instructions that, when executed by one or more
processors, causes the one or more processors to perform acts
comprising: receiving an annotation anchor that describes a region
of original content to which an annotation corresponds; receiving a
modified version of the original content; identifying one or more
key parts in the annotation anchor; identifying, based at least in
part on the one or more key parts, one or more regions of the
modified version to which the annotation potentially corresponds;
generating a score for the one or more regions; and selecting, as
the region of the modified version of the original content to which
the annotation corresponds, the identified region having the best
score.
58. One or more computer readable media as recited in claim 57,
wherein the region of original content has been altered in the
modified version.
59. One or more computer readable media as recited in claim 57,
wherein the selecting comprises: checking whether the best score
exceeds a threshold value; automatically selecting the identified
region having the best score if the best score exceeds the
threshold value; and otherwise, querying a user for input as to
whether the identified region is the region of the modified version
to which the annotation corresponds.
60. One or more computer readable media as recited in claim 57,
wherein the plurality of instructions further cause the one or more
processors to perform acts comprising: generating a new annotation
anchor based on captured features of the identified region; and
using the new annotation anchor as an anchor that describes the
region of the modified version of the original content to which the
annotation corresponds.
61. One or more computer readable media as recited in claim 57,
wherein the key parts are keywords, and wherein the plurality of
instructions further cause the one or more processors to perform
acts comprising: identifying one or more synonyms for at least one
of the one or more keywords; and altering the score for a region if
at least one of the one or more synonyms is included in the
region.
62-74. (canceled)
Description
[0001] A portion of the disclosure of this patent document contains
material which is subject to copyright protection. The copyright
owner has no objection to the facsimile reproduction by anyone of
the patent document or the patent disclosure, as it appears in the
Patent and Trademark Office patent file or records, but otherwise
reserves all copyright rights whatsoever.
TECHNICAL FIELD
[0002] This invention relates to annotating content, and more
particularly to robust anchoring of annotations to content.
BACKGROUND
[0003] As computing technology has advanced, increasingly powerful
computing devices have become available. Such devices have led to
an increase in the number of computing devices being used as well
as an expansion of the manner in which these devices are being
used. One such usage for computing devices is the generation and
distribution of electronic or digital documents.
[0004] The transition to content authoring, revising, and
distributing using computers rather than pen (or typewriter) and
paper has created many benefits, but has not been without its
problems. Some of these problems are rooted in the different manner
in which content is authored and revised on computers rather than
the more traditional paper methods. One specific problem is the
annotating of content. Paper documents have been traditionally
annotated manually, such as by highlighting or underlining of text
and/or notes written in the margin of the paper. Annotating digital
documents (e.g., documents which are being authored and revised on
a computer) in a similar manner is difficult because digital
documents are easily and frequently altered, thereby changing the
portion of the document to which the annotation corresponds. It
would thus be beneficial to provide a way to improve the manner in
which annotations are associated with portions of documents so that
the annotations are still associated with the correct portion of
the document despite alterations to the underlying content.
SUMMARY
[0005] Robust anchoring of annotations to content is described
herein.
[0006] According to one aspect, an annotation is associated with a
particular portion of content by capturing multiple features of the
portion. These features include one or more features describing a
beginning point of the portion, one or more features describing an
ending point of the portion, and one or more features describing
the portion between the beginning point and the ending point.
According to one implementation, these one or more features are
captured independently of a format used to store the content.
[0007] According to another aspect, an annotation anchor that
describes a region of content to which an annotation corresponds is
reassociated with the content (or a modified version thereof). One
or more features (for example, keywords) in the annotation anchor
are identified, and one or more candidate regions of the modified
version to which the annotation potentially corresponds are
identified. A score is generated for the one or more regions, and
the identified region having the best score is selected as the
region of the modified version of the original content to which the
annotation corresponds.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIG. 1 is a block diagram illustrating an exemplary system
for anchoring an annotation to content.
[0009] FIG. 2 illustrates exemplary content with a highlighted
portion corresponding to an annotation.
[0010] FIG. 3 illustrates an exemplary process carried out to
generate a set of one or more keywords that exist within a
region.
[0011] FIG. 4 is a flowchart illustrating an exemplary process for
generating an annotation anchor.
[0012] FIG. 5 is a flowchart illustrating an exemplary process for
re-anchoring an annotation to modified content.
[0013] FIGS. 6a, 6b, and 6c are flowcharts illustrating an
exemplary process for generating a candidate annotation region and
score corresponding to a selected keyword.
[0014] FIGS. 7, 8, 9, 10, 11, and 12 illustrate exemplary user
interfaces that may be presented by a UI module.
[0015] FIG. 13 illustrates a more general exemplary computer
environment, which can be used to implement the improved meta data
management described herein.
DETAILED DESCRIPTION
[0016] Robust anchoring of annotations to content is described
herein. For each annotation, information describing the portion of
the content to which the annotation corresponds is robustly
captured, thereby "anchoring" the annotation to the portion of the
content. This captured information, also referred to as an
"anchor", includes information regarding a beginning point of the
portion, an ending point of the portion, and the region between the
two points. Subsequently, the content (including possibly the
portion to which the annotation corresponds) can be modified, and
the annotation re-anchored to the modified content.
[0017] FIG. 1 is a block diagram illustrating an exemplary system
100 for anchoring an annotation to content. System 100 includes an
annotation marking engine 102 and an annotation re-anchoring engine
104. Engines 102 and 104 may be implemented in the same computer,
or alternatively in different computers. During operation, an
indication 106 of an annotation corresponding to underlying content
as well as the underlying content 108 are received at annotation
marking engine 102. Indication 106 includes an identification of
the portion of content 108 to which the annotation corresponds.
This identification can be made in any of a wide variety of
conventional manners, such as by identifying the page number, line
number, and character number of where the portion begins and ends.
Indication 106 can be received in any of a variety of manners. For
example, a content authoring module (not shown) may receive an
input from a user highlighting a portion of the content, and an
indication of this input forwarded to engine 102. Annotations can
correspond to a portion of content 108 explicitly identified by a
user, or alternatively a single point explicitly identified by the
user (and the portion of content 108 being implicitly
identified).
[0018] Underlying content 108 can be any of one or more types of
content, such as text content, audio content, video content, image
content, etc., or combinations of one or more of these types of
content. Underlying content 108 can be any type of content from
which one or more partially- or uniquely-identifying robust
features can be extracted. Similarly, the annotation generated by a
user can be in any of a variety of types of content (e.g., text
content, audio content, video content, image content, etc., or
combinations thereof), and need not be of the same type of content
as the underlying content 108 that it annotates. Any of a wide
variety of conventional components can be used to generate the
underlying content and/or the annotation content, including text
editors and keyboards, microphones, image capture devices, etc.
[0019] Upon receipt of indication 106, annotation marking engine
102 robustly captures the beginning point of the portion, ending
point of the portion, and region between the beginning and ending
points of the region. This capturing is performed by a beginning
point capture module 110, an ending point capture module 112, and a
region capture module 114, respectively.
[0020] FIG. 2 illustrates exemplary content with a highlighted
portion or region corresponding to an annotation. In FIG. 2, an
exemplary sentence is illustrated on a display 120 with a portion
122 highlighted. Although a dashed box is used on display 120 to
indicate highlighting, alternatively highlighting can be indicated
in a variety of other manners (such as changing the color or font
of the highlighted text, marking the area surrounding the text with
a different color, animating the text, etc.). With respect to
highlighted portion 122, the beginning point 124 of the portion is
at the letter "h" in "hardwired", the ending point 126 of the
portion is at the letter "n" in "brain", and the region 128 is the
characters between these points, inclusive (that is, "hardwired
into your brain").
[0021] For text content, the beginning point refers to the first
character in the highlighted portion, while the ending point refers
to the last character in the highlighted portion. Alternatively,
these points may be implemented in different manners. For example,
the beginning point may be the character immediately preceding the
first highlighted character, or the area between the first
highlighted character and the character immediately preceding the
first highlighted character. Similarly, the ending point may be the
character immediately succeeding the last highlighted character, or
the area between the last highlighted character and the character
immediately succeeding the last highlighted character.
[0022] Returning to FIG. 1, beginning point capture module 110
extracts one or more features regarding the beginning of the
portion to which the annotation corresponds. Any of a wide variety
of features regarding the beginning point of the portion can be
extracted. One example of such a feature is the actual characters
of the content at the beginning point (e.g., one or more characters
immediately preceding and/or succeeding the beginning point). In
one implementation, the fifteen characters before the beginning
point and the fifteen characters after the beginning point are
captured as the features of the beginning point. Another example of
such a feature is a hash value of the characters at the beginning
point (e.g., a hash value generated by using a conventional hashing
function (such as MD5 (Message Digest 5), SH-1 (Secure Hash
Algorithm-1), or other cryptographic or non-cryptographic hash
functions) to hash one or more characters immediately preceding or
succeeding the beginning point). Yet another example of such a
feature is an offset of the beginning point relative to another
point (e.g., relative to the beginning or ending of the entire
document, the beginning or ending of a particular section of the
document, etc.). Such an offset can be calculated in different
manners, such as a number of characters, a number of words, a
number of paragraphs, a number of pixels, a particular length
(e.g., number of inches) on a printed copy of the document, and so
on.
[0023] Another example of such a feature is punctuation at or near
(e.g., within a particular number of characters of) the beginning
point. Still another example of such a feature is one or more
keywords or proper nouns at or near (e.g., within a particular
number of characters of) the beginning point. Yet another example
of such a feature is dependent on the implemented document
structure (e.g., the position of the beginning point in a HyperText
Markup Language (HTML), Portable Document Format (PDF), or Rich
Text Format (RTF) parse tree).
[0024] Ending point capture module 112 extracts one or more
features regarding the ending of the portion to which the
annotation corresponds. Analogous to beginning point capture module
110, any of a wide variety of features regarding the ending point
of the portion can be extracted. In one implementation, the fifteen
characters before the ending point and the fifteen characters after
the ending point are captured as the features of the ending point.
Ending point capture module 112 may extract the same types of
features as beginning point capture module 110 (e.g., both may
capture actual characters), or different types of features (e.g.,
module 110 may capture actual characters and an offset, while
module 112 may capture a hash value of the characters and an
offset).
[0025] Region capture module 114 extracts one or more features
regarding the portion to which the annotation corresponds (that is,
the region between the beginning and ending points). Various
different features can be extracted by module 114. One such feature
is the length of the portion. This length can be expressed in
different manners, such as a character or word count, a pixel
count, a length of the portion (e.g., in inches) when printed,
etc.
[0026] Another feature that can be extracted by module 114 is a set
of one or more keywords that exist within the region. FIG. 3
illustrates an exemplary process 140 carried out by module 114 to
generate a set of one or more keywords that exist within the
region. Process 140 may optionally be implemented in software,
firmware, hardware, or a combination thereof. Initially, a
histogram that identifies word frequencies in the document is
generated (act 142). It is to be appreciated that the histogram is
generated in act 142 need only be generated once for each document
(and not every time an anchor is created). The histogram generated
in act 142 identifies, for each word in the document, the frequency
of that word (i.e., the number of times the word appears in the
document). This generation in act 142 is over the entire document,
not just the highlighted region. The words that appear in the
highlighted region are then identified (act 144). The frequency of
the words in the highlighted region are then identified from the
histogram (act 146). The frequency identified for each word in act
146 is the frequency of that word across the whole document, not
just the frequency within the highlighted region.
[0027] Once the frequencies are identified, one or more words
having the lowest frequencies are selected from the highlighted
region (act 148). The number of words selected can vary, and in one
implementation is dependent on the length of the region (e.g., the
number of selected words may be a particular percentage of the
number of words in the region). In one implementation, at least
three keywords are selected. Alternatively, a particular number of
words may not be selected, rather the words selected are those one
or more words that have the lowest frequency (and all of the words
with the lowest frequency are selected, regardless of how many
there are). For example, one region of fifteen words may have three
words that all have the lowest frequency (e.g., appearing five
times each in the document while all others appear six or more
times each), while another region of fifteen words may have only
one word with the lowest frequency (e.g., appearing three times in
the document while all others appear four or more times each). In
the first instance, all three words would be selected as keywords,
while in the second instance only the one word would be selected as
a keyword.
[0028] Returning to FIG. 1, additional features that may be
extracted from the highlighted region are the distance between the
beginning point of the region and each keyword, as well as the
distance between each keyword and the ending point of the region.
These distances can be measured in a variety of different manners,
such as characters, words, pixel counts, inches (e.g., on the
document when printed), etc. Given these distances from each
keyword to beginning and ending points, the distances between
keywords can be readily generated and used during re-anchoring, as
discussed in more detail below.
[0029] Various other features may also be extracted for the
highlighted region, such as punctuation marks within the region
(e.g., whether the beginning or ending points are located at
particular punctuation marks, such as commas, periods, or quotes),
sentence boundaries within the region (e.g., whether the beginning
point is the beginning of a sentence, or whether the ending point
is the ending of a sentence), proper nouns within the region, the
grammatical structure of the region (e.g., subject/object position
information, types of clauses within the region, etc.), an
implementation-dependent document structure (e.g., an HTML, PDF, or
RTF parse tree of the region), "fingerprinting" of the document
(e.g., generate hashes of the entire document in short segments,
then attach annotations to this "hash topography" of the document),
the semantic "meaning" of the highlighted region (e.g., using
Natural Language Processing techniques to analyze and store
information about the "meaning" of what was selected in the region,
and so forth.
[0030] Once annotation marking engine 102 has captured the various
features for the beginning point, ending point, and region
in-between these points, the captured features are output as an
annotation anchor 152. The annotation anchor thus describes various
features or aspects of the portion of content 108 to which the
annotation corresponds. Given the information in the annotation
anchor 152, the anchor 152 can be easily stored separately from the
underlying content. Alternatively, if desired, the anchor 152 could
be stored with the underlying content 108 or with the annotation
content.
[0031] The following data structures illustrate one exemplary way
in which captured data for annotation anchors can be stored. It is
to be appreciated that these are exemplary only, and that
alternative structures may also be used. TABLE-US-00001 typedef
struct _sRAnnPosInfo { sRPointInfo front; //beginning point
sRPointInfo back; //ending point KEYWORDLIST keywords; //list of
_sRKeywordInfo structures int length; //length of the annotation
region _bstr_t bkmark; //alternate bookmark for faster re-anchoring
//if underlying content did not change long offset; //offset from
the beginning of document to beginning //of annotation region }
sRAnnPosInfo; typedef struct _sRPointInfo { _bstr_t leftContent;
//the 15 characters before the point _bstr_t rightContent; //the 15
characters after the point } sRPointInfo; typedef struct
_sRKeywordInfo{ _bstr_t keyword; //the keyword int distToStart;
//distance from start of keyword to start of annotation int
distToEnd; //distance from start of keyword to end of annotation }
sRKeywordInfo;
[0032] FIG. 4 is a flowchart illustrating an exemplary process for
generating an annotation anchor. The process 160 of FIG. 4 is
carried out by annotation marking engine 102 of FIG. 1, and may be
implemented in software, firmware, hardware, or a combination
thereof.
[0033] Initially, features corresponding to the beginning point of
the annotation are captured (act 162), and features corresponding
to the ending point of the annotation are captured (act 164).
Features corresponding to the region between the beginning point
and ending point are also captured (act 166). These captured
features are then output as the annotation anchor for the
annotation (act 168).
[0034] Returning to FIG. 1, content 108 can also be input to a
content editor 154. Content editor 154 represents any device or
module capable of altering content 108. For example, content editor
154 may be a word processing application. The content 108 may be
altered by editor 154 prior to, subsequent to, or concurrently with
the marking of annotations performed by engine 102. The altered or
modified content 156 is output by editor 154 and made available to
annotation re-anchoring engine 104. Additionally, the annotation
anchors 152 from annotation marking engine 102 are also made
available to annotation re-anchoring engine 104. Re-anchoring
engine 104 uses annotation anchors 152, as well as modified content
156, to re-anchor the annotations to modified content 156,
outputting re-anchored annotations 158. Although discussed herein
primarily with reference to re-anchoring annotations to modified
content, it should be noted that annotations can be re-anchored to
unmodified content as well (or re-anchored to content that has been
stored in a different format).
[0035] An example of the altering of the underlying content as well
as the re-anchoring of annotations to the altered content is
illustrated in FIG. 2. The display 180 illustrates a sentence that
is a modified version of the sentence illustrated in display 120.
The original annotation is anchored to the highlighted portion 122
in display 120. However, since the sentence has been altered, the
exact highlighted portion 122 (the phrase "hardwired into your
brain") does not exist on display 180. Thus, annotation
re-anchoring engine 104 of FIG. 1 re-anchors the annotation to the
highlighted portion 182. Thus, even though the wording of the
underlying content has been changed, the annotation is still
anchored to the portion of the content that reflects (or closely
reflects) the same idea as was originally annotated given the
content in display 120.
[0036] Annotation re-anchoring engine 104 includes a candidate
region determination module 186, a score comparator module 188, a
user interface (UI) module 190, and a preferences module 192. For
each annotation to content 108, candidate region determination
module 186 attempts to generate a score (based on the annotation
anchor for that annotation) for one or more regions of modified
content 156 to which the annotation may potentially correspond. The
score for a candidate region reflects how well the candidate region
matches the region in the original content to which the annotation
corresponds. Score comparator module 188 analyzes the various
scores generated by candidate region determination module 186 and
attempts to identify one of those candidate regions, based on the
scores, to anchor the annotation to. Depending on the various
scores, situations may arise where the user is prompted for input
regarding where a particular annotation should be anchored. In
these situations, UI module 190 allows the user to enter such
input. Additionally, the behavior of one or more of modules 186,
188, and 190 may be user-configurable, in which case the
user-configured options are stored as preferences 192. The behavior
of annotation re-anchoring engine 104 is described in additional
detail with reference to the following figures.
[0037] FIG. 5 is a flowchart illustrating an exemplary process for
re-anchoring an annotation to modified content. The process of FIG.
5 is carried out by annotation re-anchoring engine 104 of FIG. 1
and may be implemented in software, firmware, hardware, or a
combination thereof.
[0038] Initially, an annotation anchor is received (act 222). The
keywords from the annotation anchor are identified (act 224), and
one of the keywords is selected (act 226). Any one of the keywords
can be selected in act 226 (e.g., the first one from a list stored
in the annotation anchor, one selected at random, etc.). A
candidate annotation region and score corresponding to the selected
keyword are then generated based on the location of the keyword
(act 228). If the selected keyword appears multiple times within
the modified content, then a candidate annotation region and score
is generated in act 228 for each of these multiple occurrences of
the keyword. This generation in act 228 is performed based on the
relationship of the keyword to any other keywords in the annotation
anchor as well as the beginning and ending point information in the
annotation anchor. An exemplary process for implementing act 228 is
discussed in more detail below with reference to FIGS. 6a-6c.
[0039] A check is then made as to whether the generated score
exceeds a threshold value (act 230). If the score does exceed the
threshold value then the candidate region is determined to be the
region that the annotation is to be anchored to, and the annotation
is attached to that region (act 232). Attaching the annotation to
the region refers to replacing the previous indication of the
portion of the content that the annotation previously corresponded
to with an indication of the new region. Thus, when the modified
content is subsequently displayed, the new region is highlighted
for the annotation. The specific manner in which the annotation is
attached to the region will vary by implementation, and will
typically use the same format as was used to indicate the initial
region to engine 102. The threshold value used in act 230 can vary,
but should be designed to be high enough that determination of the
correct region can be confidently made without analysis of any
additional candidate regions. For example, the threshold value may
be 98 on a scale from 0 to 100.
[0040] If the score does not exceed the threshold value in act 230,
then a check is made as to whether there are any additional
keywords that have not yet been selected (act 234). If there are
any such additional keywords than the process returns to act 226 to
select one of the remaining keywords. However, if there are no
additional keywords, then the process proceeds to identify the
largest score of those generated in act 228 (act 236). A check is
then made as to whether the largest score exceeds another threshold
value (act 238), referred to as the "guess threshold". The guess
threshold value is lower than the threshold value in act 230, but
should be designed such that there is a high level of confidence in
the determination that the candidate region is the correct region
if the candidate region's score is above the guess threshold, and
such that there is a low level of confidence in the determination
that the candidate region is the correct region if the candidate
region's score is below the guess threshold. For example, the
threshold value in act 238 may be 70 or 80 on a scale from 0 to
100.
[0041] If the identified score exceeds the threshold value in act
238, then the candidate region corresponding to the identified
score is determined to be the region that the annotation is to be
anchored to, and the annotation is attached to that region (act
240). Additionally, the information in the annotation anchor is
re-captured based on the new region the annotation is attached to
(act 242). This re-calculation comprises an annotation marking
engine (e.g., engine 102 of FIG. 1) re-capturing the various
beginning point, ending point, and region features based on the new
region that the annotation corresponds to. The history of the
annotation anchoring may also be saved with the annotation anchor
or alternatively elsewhere, allowing subsequent reference back to
the preceding one or more annotation anchors if desired. Although
not illustrated in FIG. 5, the annotation anchor may also be
re-captured after attaching the anchor to the region in act
232.
[0042] Returning to act 238, if the identified score does not
exceed the threshold value, then a check is made as to whether the
identified score is less than a lower bound (act 244), referred to
as the "orphaning threshold". This lower bound should be designed
to be less than the threshold value in act 238, and low enough that
there is little confidence in the determination that the candidate
region is the correct region. For example, the lower bound in act
244 may be 30 or 40 on a scale from 0 to 100. If the identified
score is below the lower bound, then the annotation is orphaned
(act 246). Orphaning the annotation means that the annotation is
not attached to any particular region of the content (all orphaned
annotations may be displayed, for example, at the end of the
content). However, if the identified score is greater than the
lower bound, then the user is queried regarding placement of the
annotation (act 248). In this situation, the candidate region's
score is greater than the orphaning threshold but less than the
guess threshold (there is sufficient information regarding the
candidate region to position the annotation in the document, but
not enough confidence to be sure it belongs there). For example, UI
module 190 of FIG. 1 may display to the user an indication that the
annotation is orphaned and also a "guess" button that the user can
press to cause annotation to be anchored to the highest-scoring
candidate region. Alternatively, UI module 190 may display to the
user an identification of the annotation and the candidate region,
and allow the user to input whether the region is the correct
region to which the annotation should be attached. The user may
thus identify which region is the correct region for the
annotation, or alternatively indicate that the annotation should be
orphaned.
[0043] The different threshold values discussed in acts 230 and
238, as well as the lower bound discussed in act 244, may be
user-configurable parameters (e.g., stored as preferences 192 of
FIG. 1). When these values are user-configurable parameters, UI
module 190 presents an interface to the user allowing the user to
enter inputs as to what one or more of these different values
should be. The input by the user may be specific values (e.g., the
user may enter "80" to indicate that a particular threshold amount
should have a value of 80), or alternatively the inputs may be
implicit. For example, UI 190 may present to the user an interface
querying the user as to whether the anchoring of a particular
annotation was correct. The results of one or more of such queries
may then be used by engine 104 to learn more appropriate threshold
or lower bound values. One specific example is if engine 104
automatically anchors multiple annotations because they have a
score exceeding the threshold value (e.g., 80) in act 238, but the
user indicates that many of those annotations are anchored
incorrectly, engine 104 may increase the threshold value in act 238
to (e.g., to 84) in an attempt to decrease the number of
annotations that are incorrectly anchored.
[0044] Alternatively, acts 230 and 232 may optionally be bypassed
in process 220. Acts 230 and 232 operate as a shortcut to avoid
processing numerous keywords and regions of a document if a
candidate region is found that is almost certainly the right one
(e.g., due to its very high score). Thus, acts 230 and 232 may be
removed from process 220 (although, under certain situations, this
removal may result in increased processing time to re-anchor an
annotation).
[0045] Various other modifications may also be made to the process
of FIG. 5. The process of FIG. 5 is a robust process that can
correctly identify the correct region to which an annotation should
be anchored even though the content of that region has been
changed. While the process of FIG. 5 also accurately identifies the
correct region to which an annotation should be anchored if the
content of that region has not changed, other methods may be able
to anchor annotations to unchanged content more quickly. Thus, in
an alternative embodiment, the annotation anchoring described
herein is modified to take advantage of the faster performance of
other algorithms to identify unchanged regions to which annotations
are to be anchored. In one implementation, a "getBookmark" method
used by the Microsoft Internet Explorer 5.58 web browser is used to
identify unchanged regions to which annotations are to be anchored.
Additional information regarding the "getBookmark" method is
available from Microsoft Corporation of Redmond, Wash.
[0046] FIGS. 6a-6c are flowcharts illustrating an exemplary process
228 for generating a candidate annotation region and score
corresponding to a selected keyword. The process 228 of FIGS. 6a-6c
is carried out by annotation re-anchoring engine 104 of FIG. 1, and
may be performed in software, firmware, hardware, or a combination
thereof.
[0047] Initially, given the region information from the annotation
anchor, multiple keywords in the modified content are identified
(act 260). These keywords may be identified each time process 228
is performed, or alternatively only once per annotation anchor.
[0048] The score for the selected keyword is initialized to zero
(act 262) and a check is made as to whether there are any
additional keywords in the original annotation region after the
selected keyword (act 264). The distance information stored in the
annotation anchor (e.g., distances between beginning point and
keywords and/or keywords and ending point) allows engine 104 to
determine the order of keywords in the annotation region. Thus, the
next keyword in the original annotation region (if any) can be
readily identified. If there is at least one additional keyword
after the selected keyword, a search is made through the identified
keywords in the modified content for the first occurrence of the
keyword after the selected keyword (act 266). A check is then made
as to whether including the first occurrence of the next keyword in
the candidate region would keep the length of the candidate region
less than twice the length of the original region (act 268). If so,
then 100 points are added to the score (act 270), the candidate
region is extended to include that keyword, and processing returns
to act 264. However, if including the first occurrence of the next
keyword in the candidate region would not keep the length of the
candidate region less than twice the length of the original region,
then processing returns to act 264 without adding any value to the
score and without extending the candidate region to include that
keyword.
[0049] The process continues to check whether there are any
additional keywords in the original annotation region after the
selected keyword, and adds points to the score for those keywords,
until all of the additional keywords have been analyzed (acts
264-270). In other words, if the anchor information includes a list
of n keywords, process 228 looks at all n-l other keywords for each
of the keywords identified in act 260. This accounts for the
possibility that the keywords get reordered in the modified
content. For instance, suppose keywords A, B, and C are identified
in the anchor. The process looks for all occurrences of A in the
document (act 260). For each occurrence, the process looks for
occurrences of B and C that follow it in the content. If the
process fails to find a candidate region with a high enough score,
the process looks for all occurrences of keyword B in the document.
For each occurrence, the process looks for occurrences of A and C
that follow it in the content, and so on.
[0050] After all of the additional keywords (if any) have been
analyzed, the process looks for the first beginning point (e.g.,
point 184 of FIG. 2) preceding the selected keyword, based on the
interior of the beginning point (act 272). The interior of the
beginning point refers to the area between the beginning point and
the selected keyword. The search in act 272 begins at the selected
keyword and works its way towards the beginning of the content,
analyzing each possible point along the way. The features from the
annotation anchor are compared to each possible point and a
determination made as to whether a match exists. In one
implementation, a "match" exists when the features from the
annotation anchor are the same as (identical to) the features at
the point being analyzed. For example, the 15 characters preceding
the point being analyzed are the same as the 15 characters
preceding the beginning point (and stored as a feature in the
annotation anchor). Alternatively, a "match" may exist when there
is only a partial match (e.g., a partial substring match). Any of a
variety of conventional processes may be used to determine a
partial substring match, such as AGREP. (additional information
regarding AGREP is available from the University of Arizona,
Department of Computer Science, Tucson, Ariz.).
[0051] Additionally, it should be noted that, analogous to the
discussion above regarding extracting features for a "point", the
features that distinguish a "point" need not be literal character
strings. Rather, such features could be a "fingerprint"; a weighted
collection of keywords, proper nouns, and punctuation; a character
offset; etc.
[0052] Processing then proceeds based on whether a beginning point
is located in act 272 (act 274). If a beginning point is located,
then a check is made as to whether the distance from the located
beginning point to the selected keyword exceeds the distance from
the original beginning point to the selected keyword (as indicated
in the annotation anchor) by greater than a threshold amount (e.g.,
greater than twice the original distance) (act 276). If the
distance is not exceeded by greater than the threshold amount, then
50 points are added to the score (act 278), the candidate region is
extended to include the located beginning point, and processing
proceeds to look for the first ending point succeeding the selected
keyword based on the interior of the selected keyword (act 280). If
the distance is exceeded by greater than the threshold amount, then
processing proceeds to act 280 without adding any points to the
score and without extending the candidate region to include the
located beginning point.
[0053] At act 280, the first ending point (e.g., point 185 of FIG.
2) is searched for analogous to the search for the first beginning
point in act 274, except that the search proceeds from the selected
keyword towards the end of the document. The interior of the ending
point refers to the area between the ending point and the selected
keyword. Analogous to the discussion above, a match may exist when
the features at the point being analyzed are the same as or within
a threshold amount of the features in the annotation anchor.
[0054] Processing then proceeds based on whether an ending point is
located in act 280 (act 282). If an ending point is located, then a
check is made as to whether the distance from the selected keyword
to the located ending point exceeds the distance from the selected
keyword to the original ending point (as indicated in the
annotation anchor) by greater than a threshold amount (e.g.,
greater than twice the original distance) (act 284). If the
distance is not exceeded by greater than the threshold amount, then
50 points are added to the score (act 286), the candidate region is
extended to include the located ending point, and processing
proceeds to act 288. If the distance is exceeded by greater than
the threshold amount, then processing proceeds to act 288 without
adding any points to the score and without extending the candidate
region to include the located ending point.
[0055] At act 288, a check is made as to whether the part of the
modified content preceding the located beginning point (e.g., a set
of characters, such as 15, that immediately precede the located
beginning point) matches the part of the original content preceding
the original beginning point (as indicated in the annotation
anchor). Analogous to the discussion above, a match may exist when
the features at the point being analyzed are the same as or within
a threshold amount of the features in the annotation anchor. If the
part of the modified content preceding the located beginning point
matches the part of the original content preceding the original
beginning point, then 10 points are added to the score (act 290).
If the part of the modified content preceding the located beginning
point does not match the part of the original content preceding the
original beginning point, or if there is no located beginning
point, then no points are added to the score.
[0056] Processing then proceeds with a check being made as to
whether the part of the modified content succeeding the located
ending point (e.g., a set of characters, such as 15, that
immediately succeed the located ending point) matches the part of
the original content succeeding the original ending point (as
indicated in the annotation anchor) (act 292). Analogous to the
discussion above, a match may exist when the features at the point
being analyzed are the same as or within a threshold amount of the
features in the annotation anchor. If the part of the modified
content succeeding the located ending point matches the part of the
original content succeeding the original ending point, then 10
points are added to the score (act 294). If the part of the
modified content succeeding the located ending point does not match
the part of the original content succeeding the original ending
point, or if there is no located ending point, then no points are
added to the score.
[0057] Processing then proceeds to check whether the located
beginning point is positioned in the modified content within a
threshold distance of the original beginning point (act 296). This
threshold distance (e.g., 25% of the length of the document) is the
difference in the offset of the original beginning point from a
particular point (e.g., the beginning of the document), and the
offset of the located beginning point from the particular point. If
the located beginning point is positioned in the modified content
within a threshold distance of the original beginning point, then
20 points are added to the score (act 298) and processing proceeds
to act 300. However, if the located beginning point is not
positioned in the modified content within a threshold distance of
the original beginning point, then processing proceeds to act 300
without adding any points to the score. In one implementation, a
number of points between zero and 20 are assigned based on how far
the point has moved (its position in the original content compared
to its position in the modified content), using a sliding scale
scoring process as discussed in more detail below.
[0058] The addition of points in act 298 is performed to
distinguish between an "acceptable" choice and a "really good"
choice. For example, suppose that an annotation is attached to the
word "the" in a document. The word "the" is repeated several times
throughout the document, so several candidate regions are
identified, all of which are more or less equally likely to be the
correct candidate region. By storing the distance of the original
beginning point from the beginning of the original document, this
helps the process identify the correct occurrence of "the" and
discount the other occurrences from being correct.
[0059] At act 300, a check is made as to whether the length of the
annotation region (from located beginning point to located ending
point) has changed by greater than a threshold amount (e.g.,
increased by more than twice the original length or decreased by
more than one-half the original length). If the length has not
changed by greater than the threshold amount, then 50 points are
added to the score (act 302); otherwise, no points are added to the
score. If no beginning point is located (in act 272) and/or no
ending point is located (in act 280), then no points are added to
the score. If no beginning point is located then a default
beginning point is determined to be the beginning of the first
keyword identified and included in the candidate region. Similarly,
if no end point is located, then a default ending point is
determined to be the end of the last keyword identified and
included in the candidate region.
[0060] Processing then proceeds to act 304, where the score is
normalized by the maximum possible score for the keyword (which
will vary based on the number of keywords in the annotation
region). In one implementation, the score is normalized to a scale
of 0 to 100. The maximum possible score (MaxScore) for a candidate
region is determined as follows: MaxScore=(keywordWeight.times.(no.
of
keywords-1))+(2.times.endPointWeight)+(2.times.contextWeight)+offsetWeigh-
t+lengthWeight where keywordWeight is the number of points added
for locating a keyword that keeps the range within the desired
length (100 points in acts 270 and 278), no. of keywords is the
number of keywords indicated in the anchor as being in the region,
endPointWeight is the number of points added for locating each of
the beginning point and the ending point within the desired
distance (50 points each in acts 278 and 286), contextWeight is the
number of points added for the context of the located beginning
point (the area preceding the beginning point) and the ending point
(the area succeeding the ending point) matching the original
context (10 points each in acts 290 and 294), offset Weight is the
number of points added for the located beginning point being
positioned as desired (20 points in act 298), and length Weight is
the number of points added for the length of the annotation region
not changing more than the desired amount (50 points in act
302).
[0061] In the discussion above regarding FIGS. 6a-6c, reference is
made to particular point values (e.g., in acts 270, 278, 286, 290,
294, 298, and 302). It is to be appreciated that these specific
point values are exemplary only, and that different point values
could be used.
[0062] Also in the discussion above regarding FIGS. 6a-6c, various
checks are made and either a full number of points are added to the
score or zero points are added to the score depending on the
outcome of the check. Alternatively, rather than having either all
or zero points awarded based on the outcome of a check, a sliding
scale may be implemented that assigns different points ranging from
zero up to all points based on how well the checked value compares
to the original value. For example, in checks where distances are
involved (e.g., the length of the annotation region, or offset of
the beginning point from a particular point in the content), the
actual score (Score) may be determined as follows:
Score=weight.times.((maxDiff-diffAmt.sup.1.2)/maxDiff) where weight
is the maximum number of points that may be assigned, maxDiff is
the maximum possible difference, and diffAmt is the amount of
difference between the two distances. The value diffAmt is raised
to power 1.2 so that the score goes down by more as the amount of
the difference gets larger. In one implementation, if the value of
diffAmt.sup.1.2 is greater than the value of maxDiff, then the
value of Score is set to zero.
[0063] Various other modifications may also be made to the process
of FIGS. 6a-6c. In one implementation, the surrounding context of
an original beginning point and/or ending point can be used to
assist in locating a beginning point and/or ending point in the
modified content. For example, rather than relying solely on the
interior of the beginning point in determining the location of a
beginning point (in act 272), the exterior of the beginning point
(the area immediately preceding the beginning point) may be used to
compare against the area immediately preceding the original
beginning point. If the comparison results in a match, then the
beginning point may be located even if the interior of the
beginning point is not a match. An analogous process may be used
for the ending point, except that the exterior of the ending point
refers to the area immediately succeeding the ending point. Note,
however, that beginning and ending points located based on the
surrounding context may be given a lower weight than a beginning
and ending points located based on the interior.
[0064] Another modification that may be made is to expand anchors
to a particular default point if the beginning point or ending
point cannot be located. The particular point can vary based on the
type of annotation made (e.g., implicit or explicit), and may be,
for example, the beginning or ending of a sentence, the beginning
or ending of a paragraph, the beginning or ending of a section,
etc. By way of example, if an annotation is anchored to a portion
of a sentence in the original content, but the ending point in the
modified content cannot be located, then the end of the sentence
that includes the last keyword (the last keyword that still keeps
the candidate region within the desired length) may be used as the
located ending point (although the number of points added in act
286 may be reduced to reflect the manner in which the ending point
was located). By way of another example, if an annotation is
anchored to a portion of a sentence in the original content, but
the beginning point in the modified content cannot be located, then
the beginning of the sentence that includes the selected keyword
may be used as the located beginning point (although the number of
points added in act 278 may be reduced to reflect the manner in
which the beginning point was located).
[0065] Another modification that may be made is to expand what
words are used as keywords. For example, proper names may be used
as keywords, or capitalized words (other than those at the
beginning of a sentence) may be used as keywords, or words in
quotation marks may be used as keywords. Punctuation may also be
used as a keyword. Certain punctuation marks may be pre-determined
or user-selected as being keywords (e.g., exclamation points,
question marks, quotation marks, etc.), or alternatively histograms
of punctuation frequency may be generated analogous to those of
word frequency discussed above. Additionally, the "keywords" may be
limited to only letters, or may include both letters and numbers,
and optionally include other characters (for example, the
ampersand, section mark, etc.).
[0066] As discussed above with reference to FIG. 5, the user may be
queried for input as to whether the proposed region for anchoring
an annotation is correct. The proposed region may be identified to
the user in any of a variety of manners, such as displaying to the
user the actual content in the region, or highlighting the region
in the modified content. This interface may allow the user to
simply indicate "yes" or "no", or alternatively have the user
manually select the region of the modified content to which the
annotation should be anchored. Alternatively, the user may be
allowed to cycle through multiple different proposed regions and
select which of those regions is the correct region to which the
annotation should be anchored.
[0067] Another modification that may be made is to expand on the
semantics of the region, such as using a thesaurus to expand a
particular keyword. For example, if the next keyword after the
selected keyword is not found in act 266, or would be outside the
desired range in act 268, then additional acts may be performed to
lookup synonyms for the keyword in a thesaurus. These synonyms are
then searched for and a determination made as to whether they are
within the desired range (analogous to acts 266 and 268). If a
synonym is within the desired range, then an appropriate number of
points can be added to the score (analogous to act 270). The number
of points may optionally be less than the number that would have
been added if the original keyword were found rather than a
synonym. Analogous to synonyms, antonyms may also be searched for
(e.g., the word "yes" has been replaced by the word "no", or the
word "beginning" has been replaced by the word "ending"), although
the number of points added for finding an antonym would optionally
be less than the number added for finding a synonym.
[0068] Another modification may be made to attempt to identify
possible split regions. A split region refers to the region the
annotation is originally anchored to being split into two or more
parts and additional content inserted between the parts. This can
result in low scores for the different parts of the annotation
because the remaining parts do not satisfy many of the distance
tests that are performed (e.g., length of the entire region,
distance from a keyword to the beginning point or ending point,
etc.). In this situation, the various data and scores can be
analyzed to attempt to determine such a split. This analysis to
identify a split region may always be performed, or alternatively
only sometimes (e.g., if the annotation would otherwise be
orphaned). In performing the analysis, annotation re-anchoring
engine 104 looks for "pieces" of the annotation region, such as the
beginning point followed by one or more keywords, and one or more
other keywords followed by the ending point. If such pieces are
located, engine 104 treats the entire split region (including the
additional content inserted between the two pieces) as the
annotation region.
[0069] Alternatively, each of the individual pieces may be treated
as an individual annotation region (thus splitting the original
annotation into two annotations). Intermediate points can be
generated for split regions in much the same way that beginning and
ending points are generated, except that the intermediate points
are generated within the interior of the selected region around
"significant" intermediate features, such as periods and commas
(which are likely to serve as cleaving points where a whole
sentence or phrase may be separated from the preceding or
succeeding sentence or phrase). These intermediate points are
generated when the beginning and ending point features are captured
(e.g., by annotation marking engine 102 of FIG. 1), but can be left
out of most processing by annotation re-anchoring engine 104 unless
splitting is suspected. As intermediate points are found, they can
serve as ending/beginning points for the new regions resulting from
the split.
[0070] In addition, the discussion above refers to generating
scores for different candidate regions with the highest score being
indicative of the closest match to the original region the
annotation was anchored to (and thus the best score).
Alternatively, different scoring methods may be used so that the
lowest score is the best score and indicative of the closest match
(e.g., rather than adding points in acts 270, 278, 286, 290, 294,
298, and 302, points can be subtracted).
[0071] Various modifications can also be made to improve the
efficiency of the processes described above. For example, as
discussed with reference to act 142 of FIG. 3, the histogram need
only be generated once per document. By way of another example, the
indexing of keywords in the modified content (act 260 of FIG. 6a)
need only be performed once for the content (and not repeated for
each keyword in an annotation anchor). By way of another example,
once a particular lo keyword is located in the modified content for
re-anchoring one annotation, it need not be re-located when
re-anchoring additional annotations.
[0072] FIG. 7 illustrates an exemplary user interface 330 that may
be presented by UI module 190 of FIG. 1. The interface 330 includes
an annotation display window 332 in which the content of the
candidate region(s) can be displayed. Although illustrated as
showing only one candidate region at a time, alternatively multiple
regions may be displayed in window 332 concurrently. A region
identification portion 334 identifies which candidate region is
currently being displayed in window 332 as well as the total number
of candidate regions. Multiple user-selectable buttons 336, 338,
340, and 342 are also included in interface 330. Show next region
button 336 causes, upon selection, UI module 190 to display in
window 332 the next candidate-region. Regions can be ordered in any
manner, such as from highest score to lowest score. Select current
region button 338 causes, upon selection, UI module 190 to record
the candidate region currently being displayed as the region to
which the annotation is to be anchored. Show region in document 340
causes, upon selection, UI module 190 to display the underlying
content and draw attention to (e.g., highlight) the candidate
region within the underlying content. UI module 190 may display the
underlying content in window 332, or alternatively open another
user interface window for display of the content (or alternatively
take some other action, such as print out the underlying content
with the candidate region underlined). Cancel button 342 causes,
upon selection, UI module 190 to close window 330 and terminate the
querying process for the current annotation anchor. In one
implementation, if the querying process is terminated without user
selection of a candidate region, the annotation is orphaned.
[0073] Additional information (not shown) may also be optionally
included in interface 330. For example, the score of the region
currently being displayed in window 332 may also be displayed, the
range of scores for the candidate regions may be displayed, an
indication of important aspects that could not be located for the
candidate region may be displayed (e.g., an indication that a
beginning point or an ending point could not be found, or that a
particular keyword could not be found), an indication of which
keywords were found within the candidate region, and so forth.
[0074] Interface 330 is intended to be exemplary only. The
components of interface 330 can be changed to be any of a wide
variety of conventional user interface components. For example,
rather than buttons 336-342, one or more pull-down menus may be
included that illustrate user-selectable inputs, one or more check
boxes and an "ok" button may be used for the inputs, and so
forth.
[0075] Additionally, UI module 190 may present an interface to the
user that lets the user adjust the region of the modified content
to which the annotation is re-anchored. For example, the
re-anchoring process may identify a region of the modified content
which the user believes is too long or too short at the beginning
and/or ending. UI module 190 can present an interface that lets the
user re-highlight the portion of the modified content to which he
or she desires to have the annotation anchored. This can be done,
for example, in window 332 of FIG. 7, or alternatively a separate
window or dialog box. The user may be allowed to manually
re-highlight the desired region, or alternatively may be allowed to
input relocation commands to UI module 190 (e.g., enter a number
into a data entry field and then click a button to "extend ending"
by the entered number of characters or words, "shorten beginning"
by the entered number of characters or words, etc.). Any such
changes are then stored so that the annotation is attached to this
re-highlighted portion.
[0076] FIGS. 8-12 illustrate additional exemplary user interfaces
that may be presented by UI module 190 of FIG. 1. FIG. 8
illustrates an interface 350 displaying a web page 352 (e.g.,
written using HTML or XML) with highlighted (shaded) annotations
made on it. Highlighted region 354 is a "highlight" annotation with
no additional content to it (e.g., nothing extra typed-in by the
user as annotation content), while highlighted regions 356 and 358
are "note" annotations with some content. On the left hand side an
annotation display portion 360 displays an index showing, among
other things, the keywords that were chosen from the highlighted
regions and their respective anchoring scores (all 100 because they
were all created on this web page). The information (e.g., keywords
and scores) 354', 356', and 358' in portion 360 correspond to
regions 354, 356, and 358, respectively.
[0077] FIG. 9 illustrates interface 350 displaying a page 368 that
is a modified version of the original web page 352 of FIG. 8. On
page 368, the highlight annotation 354 has been orphaned, and this
is indicated in annotation display portion 370 (its score is less
than the higher guess threshold, but greater than the lower orphan
threshold). The note annotations 356 and 358 have both been found
and repositioned correctly, however note that the region that is
highlighted for note annotation 356 in the modified document 368 is
slightly different from the region that was highlighted for it in
the original document 352.
[0078] FIG. 10 illustrates interface 350 displaying page 368 and is
the same as FIG. 9 except that the index pane (annotation display
portion 370) on the left hand side has been scrolled to show the
details for the two note annotations 356 and 358. Note annotation
356 has a less-than-perfect score due to the region with which it
is associated being slightly different from the region it was
originally anchored to. Note annotation 358 also has a score of
less than 100 (due, for example, to changes in location of the
region with which it is associated having shifted slightly due to
alterations in the content of the modified version).
[0079] FIG. 11 illustrates interface 350 displaying page 368 and is
similar to FIG. 9, but shows the modified web page 368 after the
"guess" button 374 in portion 370 has been pressed for the orphaned
annotation. The "best guess" candidate region 376 is displayed on
page 368, indicating the candidate region that the process
identified as being the most likely region to which the orphaned
annotation corresponds. The information (e.g., keywords and score)
376' in portion 370 corresponds to region 376.
[0080] FIG. 12 illustrates interface 350 displaying page 368 and is
similar to FIG. 11, but shows modified web page 368 after the "best
guess" candidate region has been selected as the new location for
the highlight annotation and the "reattach" button 378 of FIG. 11
has been pressed. The "reattach" button 378 causes the process to
calculate new anchor statistics for the highlight annotation based
on the newly selected region 376 and stores them with the
annotation. The score for the previously orphaned annotation is now
100 as it is now treated as having been created on web page
368.
[0081] FIG. 13 illustrates a more general exemplary computer
environment 400, which can be used to implement the improved meta
data management described herein. The computer environment 400 is
only one example of a computing environment and is not intended to
suggest any limitation as to the scope of use or functionality of
the computer and network architectures. Neither should the computer
environment 400 be interpreted as having any dependency or
requirement relating to any one or combination of components
illustrated in the exemplary computer environment 400.
[0082] Computer environment 400 includes a general-purpose
computing device in the form of a computer 402. Computer 402 can
be, for example, a device implementing annotation marking engine
102, annotation re-anchoring module 104, or content editor 154 of
FIG. 1. The components of computer 402 can include, but are not
limited to, one or more processors or processing units 404, a
system memory 406, and a system bus 408 that couples various system
components including the processor 404 to the system memory
406.
[0083] The system bus 408 represents one or more of any of several
types of bus structures, including a memory bus or memory
controller, a peripheral bus, an accelerated graphics port, and a
processor or local bus using any of a variety of bus architectures.
By way of example, such architectures can include an Industry
Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA)
bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards
Association (VESA) local bus, and a Peripheral Component
Interconnects (PCI) bus also known as a Mezzanine bus.
[0084] Computer 402 typically includes a variety of computer
readable media. Such media can be any available media that is
accessible by computer 402 and includes both volatile and
non-volatile media, removable and non-removable media.
[0085] The system memory 406 includes computer readable media in
the form of volatile memory, such as random access memory (RAM)
410, and/or non-volatile memory, such as read only memory (ROM)
412. A basic input/output system (BIOS) 414, containing the basic
routines that help to transfer information between elements within
computer 402, such as during start-up, is stored in ROM 412. RAM
410 typically contains data and/or program modules that are
immediately accessible to and/or presently operated on by the
processing unit 404.
[0086] Computer 402 may also include other removable/non-removable,
volatile/non-volatile computer storage media. By way of example,
FIG. 13 illustrates a hard disk drive 416 for reading from and
writing to a non-removable, non-volatile magnetic media (not
shown), a magnetic disk drive 418 for reading from and writing to a
removable, non-volatile magnetic disk 420 (e.g., a "floppy disk"),
and an optical disc drive 422 for reading from and/or writing to a
removable, non-volatile optical disc 424 such as a CD-ROM, DVD-ROM,
or other optical media. The hard disk drive 416, magnetic disk
drive 418, and optical disc drive 422 are each connected to the
system bus 408 by one or more data media interfaces 426.
Alternatively, the hard disk drive 416, magnetic disk drive 418,
and optical disc drive 422 can be connected to the system bus 408
by one or more interfaces (not shown).
[0087] The various drives and their associated computer-readable
media provide non-volatile storage of computer readable
instructions, data structures, program modules, and other data for
computer 402. Although the example illustrates a hard disk 416, a
removable magnetic disk 420, and a removable optical disc 424, it
is to be appreciated that other types of computer readable media
which can store data that is accessible by a computer, such as
magnetic cassettes or other magnetic storage devices, flash memory
cards, CD-ROM, digital versatile discs (DVD) or other optical
storage, random access memories (RAM), read only memories (ROM),
electrically erasable programmable read-only memory (EEPROM), and
the like, can also be utilized to implement the exemplary computing
system and environment.
[0088] Any number of program modules can be stored on the hard disk
416, magnetic disk 420, optical disc 424, ROM 412, and/or RAM 410,
including by way of example, an operating system 426, one or more
application programs 428, other program modules 430, and program
data 432. Each of such operating system 426, one or more
application programs 428., other program modules 430, and program
data 432 (or some combination thereof) may implement all or part of
the resident components that support the distributed file
system.
[0089] A user can enter commands and information into computer 402
via input devices such as a keyboard 434 and a pointing device 436
(e.g., a "mouse"). Other input devices 438 (not shown specifically)
may include a microphone, joystick, game pad, satellite dish,
serial port, scanner, and/or the like. These and other input
devices are connected to the processing unit 404 via input/output
interfaces 440 that are coupled to the system bus 408, but may be
connected by other interface and bus structures, such as a parallel
port, game port, or a universal serial bus (USB).
[0090] A monitor 442 or other type of display device can also be
connected to the system bus 408 via an interface, such as a video
adapter 444. In addition to the monitor 442, other output
peripheral devices can include components such as speakers (not
shown) and a printer 446 which can be connected to computer 402 via
the input/output interfaces 440.
[0091] Computer 402 can operate in a networked environment using
logical connections to one or more remote computers, such as a
remote computing device 448. By way of example, the remote
computing device 448 can be a personal computer, portable computer,
a server, a router, a network computer, a peer device or other
common network node, and the like. The remote computing device 448
is illustrated as a portable computer that can include many or all
of the elements and features described herein relative to computer
402.
[0092] Logical connections between computer 402 and the remote
computer 448 are depicted as a local area network (LAN) 450 and a
general wide area network (WAN) 452. Such networking environments
are commonplace in offices, enterprise-wide computer networks,
intranets, and the Internet.
[0093] When implemented in a LAN networking environment, the
computer 402 is connected to a local network 450 via a network
interface or adapter 454. When implemented in a WAN networking
environment, the computer 402 typically includes a modem 456 or
other means for establishing communications over the wide network
452. The modem 456, which can be internal or external to computer
402, can be connected to the system bus 408 via the input/output
interfaces 440 or other appropriate mechanisms. It is to be
appreciated that the illustrated network connections are exemplary
and that other means of establishing communication link(s) between
the computers 402 and 448 can be employed.
[0094] In a networked environment, such as that illustrated with
computing environment 400, program modules depicted relative to the
computer 402, or portions thereof, may be stored in a remote memory
storage device. By way of example, remote application programs 458
reside on a memory device of remote computer 448. For purposes of
illustration, application programs and other executable program
components such as the operating system are illustrated herein as
discrete blocks, although it is recognized that such programs and
components reside at various times in different storage components
of the computing device 402, and are executed by the data
processor(s) of the computer.
[0095] Computer 402 typically includes at least some form of
computer readable media. Computer readable media can be any
available media that can be accessed by computer 402. By way of
example, and not limitation, computer readable media may comprise
computer storage media and communication media. Computer storage
media includes volatile and nonvolatile, removable and
non-removable media implemented in any method or technology for
storage of information such as computer readable instructions, data
structures, program modules or other data. Computer storage media
includes, but is not limited to, RAM, ROM, EEPROM, flash memory or
other memory technology, CD-ROM, digital versatile discs (DVD) or
other optical storage, magnetic cassettes, magnetic tape, magnetic
disk storage or other magnetic storage devices, or any other media
which can be used to store the desired information and which can be
accessed by computer 402. Communication media typically embodies
computer readable instructions, data structures, program modules or
other data in a modulated data signal such as a carrier wave or
other transport mechanism and includes any information delivery
media. The term "modulated data signal" means a signal that has one
or more of its characteristics set or changed in such a manner as
to encode information in the signal. By way of example, and not
limitation, communication media includes wired media such as wired
network or direct-wired connection, and wireless media such as
acoustic, RF, infrared and other wireless media. Combinations of
any of the above should also be included within the scope of
computer readable media.
[0096] The invention has been described herein in part in the
general context of computer-executable instructions, such as
program modules, executed by one or more computers or other
devices. Generally, program modules include routines, programs,
objects, components, data structures, etc. that perform particular
tasks or implement particular abstract data types. Typically the
functionality of the program modules may be combined or distributed
as desired in various embodiments.
[0097] For purposes of illustration, programs and other executable
program components such as the operating system are illustrated
herein as discrete blocks, although it is recognized that such
programs and components reside at various times in different
storage components of the computer, and are executed by the data
processor(s) of the computer.
[0098] Alternatively, the invention may be implemented in hardware
or a combination of hardware, software, and/or firmware. For
example, one or more application specific integrated circuits
(ASICs) could be designed or programmed to carry out the
invention.
[0099] It should be noted that the annotation anchoring described
herein captures features of the underlying content to which the
annotation corresponds, and uses these captured features for
re-anchoring the annotation to the content after it has is been
modified. The anchor information is independent of the underlying
content--no changes or additions to the underlying content need be
made in order to generate the annotation anchor (e.g., no tags or
markers need be inserted into the underlying content to indicate
where in the underlying content the annotation is to be
anchored).
[0100] It should further be noted that the annotation anchoring
described herein is not tied to any particular content format. For
example, various different formats exist for storing content, such
as the Microsoft Word word processing document format, the HTML
format, the Tagged Image File Format (TIFF), RTF, PDF, etc. The
annotation anchors are generated based on captured features from
the original language-level content, and, depending on the features
extracted, need involve no format-specific structural analysis of
the document, so even if the content were to be modified and
changed to a different format, the annotation could still be
re-anchored to the new format.
[0101] The anchoring and re-anchoring described herein is discussed
primarily with reference to text content. However, it is to be
appreciated that the anchoring and re-anchoring can be used with a
wide variety of types of content. With different types of content,
different characteristics of the content may be used analogously to
the keywords discussed above. These different key parts of the
content will vary based on the content type (e.g., keywords for
text content, shot boundaries for video content, etc.).
[0102] By way of example, the underlying content 108 of FIG. 1
could be video content with each frame of video content being
treated as analogous to characters in text content. The beginning
point of a region of video content may be identified by capturing
the frame number of the first frame in the region, by capturing
color histograms calculated from the first five frames preceding
and succeeding the beginning point, etc. Similarly, the ending
point of a region of video content may be identified by capturing
the frame number of the last frame in the region, by capturing
color histograms calculated from the first five frames preceding
and succeeding the ending point, etc. For the region between the
beginning and ending points, various features may be captured such
as the number of frames between the two points, drastic changes in
video may be identified using conventional shot boundary detection
techniques and these shot boundaries used analogously to text
keywords, etc. An example of such a shot boundary detection
technique is discussed in Yong Rui, Thomas S. Huang, and Sharad
Mehrotra, Constructing Table-of-Content for Videos, ACM Multimedia
Systems Journal, Special Issue Multimedia Systems on Video
Libraries, Vol. 7, No. 5, September 1999, pp 359-368.
[0103] By way of another example, the underlying content 108 of
FIG. 1 could be a single image with each pixel in the image being
treated as analogous to characters in text content. For image
content, rather than a set of sequential bits being the region, a
2-dimensional shape (e.g., a rectangle, circle, triangle, etc.) may
be used to define the annotation region. Points on the
2-dimensional shape can be treated analogously to the beginning and
ending points (e.g., the top left corner of the rectangle may be
the beginning point and the lower right corner of the rectangle may
be the ending point), and actual pixel values, hashes of pixel
values, pixel offsets (e.g., from a particular point, such as an
origin), etc. may be calculated. Various features can be captured
for the region, such as a color histogram, number of pixels in the
region, recognizable/trackable objects in the region, motion flow,
edge features, wavelet signatures, or various other standard image
processing features. These features can then be used to re-anchor
the annotation to the correct portion of the image (e.g., a
particular individual's face in the image) despite changes in
resolution of the image, cropping of the image, etc.
[0104] By way of yet another example, the underlying content 108 of
FIG. 1 could be audio content. Audio content in digital form can be
separated into multiple frames or samples (or groups of frames and
samples), and various features captured therefrom to be used to
anchor annotations to the audio content. In the case of analog
audio content, the analog audio can be digitized into digital form
in a conventional manner (which generates multiple samples). The
beginning point of a region of audio content may be identified by
capturing the frame or sample number of the first frame or sample
in the region, by capturing the values of a number of frames or
samples preceding and succeeding the beginning point (e.g., 50 ms
of audio data preceding and succeeding the beginning point), by
extracting any of various features commonly used in conventional
speech or audio processing programs, such as Fast Fourier Transform
(FFT) to generate frequency-domain features from the audio segment,
or Mel Frequency Coefficients (MFCC), etc. Similarly, the ending
point of a region of audio content may be identified by capturing
the frame or sample number of the last frame or sample in the
region, by capturing the values of a number of frames or samples
preceding and succeeding the ending point (e.g., 50 ms of audio
data preceding and succeeding the ending point), by extracting any
of various features commonly used in conventional speech or audio
processing programs, etc. For the region between the beginning and
ending points, various features may be captured such as the number
of frames or samples between the two points, drastic changes in
audio characteristics (e.g., changes in volume) may be identified
using conventional techniques and used analogously to text
keywords, a signature corresponding to silence/pause intervals in
the region may be generated, etc.
[0105] Additionally, the anchoring and re-anchoring described
herein is discussed primarily with respect to explicit annotation
region identification by a user (for example, the user highlighting
or underling a particular series of words in text content).
However, the anchoring and re-anchoring is also applicable to
implicit region identification. For example, a user may make a mark
in a margin next to a paragraph and enter an annotation associated
with that mark. For implicit region identification, various
features can be captured to represent the beginning point, ending
point, and region between the points to which the annotation is to
be anchored. Examples of such features include the closest section
heading preceding or succeeding the mark, the number(s) of the
paragraph(s) the mark is closest to, the page number of the mark,
hash values of characters near the mark, and so forth. For example,
the closest preceding section heading and page number may be
features used for the beginning point, the closest succeeding
section heading and paragraph number may be features used for the
ending point, and a hash value (one per paragraph) calculated by
hashing each of the paragraph(s) closest to the mark may be used
analogously to the keywords discussed above.
[0106] In addition, an explicit region may be automatically
generated based on the implicit proximity of the annotation to the
content. For example, if the implicitly positioned annotation is
"near" the third paragraph, choose the third paragraph as the
region to which the annotation is anchored, and generate robust
features from the third paragraph (as if the user had selected the
third paragraph as the region to which the annotation
corresponds).
Conclusion
[0107] Although the description above uses language that is
specific to structural features and/or methodological acts, it is
to be understood that the invention defined in the appended claims
is not limited to the specific features or acts described. Rather,
the specific features and acts are disclosed as exemplary forms of
implementing the invention.
* * * * *