U.S. patent application number 14/859362 was filed with the patent office on 2016-01-14 for document assembly systems and methods.
This patent application is currently assigned to Lexprompt, LLC. The applicant listed for this patent is Lexprompt, LLC. Invention is credited to Dmitry Gurenich, Lev Rosenblum, Gianni Taraschi.
Application Number | 20160012021 14/859362 |
Document ID | / |
Family ID | 47354763 |
Filed Date | 2016-01-14 |
United States Patent
Application |
20160012021 |
Kind Code |
A1 |
Rosenblum; Lev ; et
al. |
January 14, 2016 |
DOCUMENT ASSEMBLY SYSTEMS AND METHODS
Abstract
Embodiments of the present invention relate to devices, systems,
and methods for assembling and/or creating documents with the aid
of a computer system. One or more embodiments provide document
assembly systems and methods. More specifically, the document
assembly system may allow the user to retrieve relevant texts or
text segments, which have been previously created, and may allow
the user to incorporate such texts and/or text segments into a
document.
Inventors: |
Rosenblum; Lev; (Salt Lake
City, UT) ; Taraschi; Gianni; (Arlington, MA)
; Gurenich; Dmitry; (Brookline, MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Lexprompt, LLC |
Salt Lake City |
UT |
US |
|
|
Assignee: |
Lexprompt, LLC
Salt Lake City
UT
|
Family ID: |
47354763 |
Appl. No.: |
14/859362 |
Filed: |
September 21, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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13525359 |
Jun 18, 2012 |
9164962 |
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14859362 |
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61499137 |
Jun 20, 2011 |
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Current U.S.
Class: |
715/271 |
Current CPC
Class: |
G06F 40/166 20200101;
G06F 40/131 20200101; G06F 40/205 20200101; G06F 40/10
20200101 |
International
Class: |
G06F 17/22 20060101
G06F017/22; G06F 17/27 20060101 G06F017/27; G06F 17/24 20060101
G06F017/24 |
Claims
1. A computer system for assembling a document, the computer system
comprising: one or more processors; a system memory; a display
capable of providing information to a user, the display controlled
by the one or more processors; and one or more computer-readable
storage media having stored thereon computer-executable
instructions that, when executed by the one or more processors
perform the acts of: receiving an entry from the user that is
selected by highlighting text in the document, the entry comprising
the highlighted text in the document; after receiving the entry,
retrieving a plurality of relevant texts from stored text,
retrieving the plurality of relevant texts being at least partially
based on the entry received from the user; after retrieving the
plurality of relevant texts from the stored text, displaying the
relevant texts on the display; after displaying the retrieved
relevant texts on the display, receiving at least one selection of
the relevant texts from the user; and after receiving the at least
one selection of the relevant text, adding to the document the
relevant text from the at least one received selection of the
relevant texts.
2. The computer system of claim 1, wherein the acts further
comprise removing at least one named entity from the stored text
before receiving the entry from the user.
3. The computer system of claim 2, wherein removing at least one
named entity from the stored text includes tagging.
4. The computer system of claim 1, wherein the act of adding to the
document the relevant text from the at least one received selection
of the relevant texts comprises adding the received at least one
selection of the relevant texts to a selected location in the
document.
5. The computer system of claim 1, wherein the relevant texts and
the document are displayed concurrently on the display.
6. The computer system of claim 1, wherein the displayed relevant
texts are ranked based on one or more predetermined metrics.
7. The computer system of claim 6, wherein the ranking is at least
in part based on a readability metric of the relevant texts.
8. The computer system of claim 1, wherein the entry from the user
includes text entered by the user in the document.
9. The computer system of claim 8, wherein the text entered by the
user in the document includes at least one spoken word transcribed
to text.
10. The computer system of claim 2, wherein the at least one named
entity removed from the stored text that is in the relevant text
from the at least one received selection is automatically replaced
with a current named entity from a named entity storage.
11. The computer system of claim 1, wherein the acts further
comprise parsing previously created documents to obtain stored
text.
12. The computer system of claim 11, wherein the stored text
comprises one or more of paragraphs, sentence sequences, sentences,
and sentence chunks.
13. The computer system of claim 12, wherein the one or more of
paragraphs, sentence sequences, sentences, and sentence chunks are
in storage clusters based on predetermined parameters.
14. A computer program product comprising one or more
computer-readable storage media having stored thereon
computer-executable instructions that, when executed by one or more
processors of a computer system, cause the computer system to
perform acts of: receiving an entry from the user that is selected
by highlighting text in the document, the entry comprising the
highlighted text in the document; after receiving the entry,
retrieving a plurality of relevant texts from stored text,
retrieving the plurality of relevant texts being at least partially
based on the received entry received from the user; after
retrieving the plurality of relevant texts from the stored text,
displaying the relevant texts on a display; after displaying the
retrieved relevant texts on the display, receiving at least one
selection of the relevant texts from the user; and after receiving
the at least one selection of the relevant text, adding to the
document the relevant text from the at least one received selection
of the relevant texts.
15. The computer program product of claim 14, wherein the acts
further comprise: an act of parsing previously created documents to
obtain one or more of paragraphs, sentence sequences, sentences,
and sentence chunks; and an act of adding one or more of
paragraphs, sentence sequences, sentences, and sentence chunks into
a database to create the stored text.
16. The computer system of claim 14, wherein the received at least
one word entry from the user includes text entered by the user in
the document.
17-18. (canceled)
19. A computer system for assembling a document, the computer
system comprising: one or more processors; a system memory; a
display capable of providing information to a user, the display
controlled by the one or more processors; and one or more
computer-readable storage media having stored thereon
computer-executable instructions that, when executed by the one or
more processors perform the acts of: receiving an entry from the
user that is selected by highlighting text in the document, the
entry comprising the highlighted text in the document; after
receiving the entry, retrieving a plurality of relevant texts from
stored text, retrieving the plurality of relevant texts being at
least partially based on the entry received from the user; after
retrieving the plurality of relevant texts from the stored text,
displaying the relevant texts on the display concurrently with the
text in the document; and ranking the relevant texts at least in
part based on a readability metric.
20. The computer system of claim 19, wherein the readability metric
is based on average use of a chunk of a sentence in the stored
text.
21. The computer system of claim 19, wherein the acts further
comprise: after displaying the at least one of the retrieved
relevant texts on the display, receiving at least one selection of
the relevant texts from the user; and after receiving the at least
one selection of the relevant text, adding to the document the
relevant text from the at least one received selection of the
relevant texts.
22. The computer system of claim 19, wherein the received at least
one word entry from the user includes text entered by the user in
the document.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation application of and claims
priority to U.S. patent application Ser. No. 13/525,359, which
claims priority to U.S. Provisional Patent Application No.
61/499,137, filed Jun. 20, 2011, the entire content of each of the
foregoing applications is incorporated by this reference.
BACKGROUND OF THE INVENTION
[0002] 1. The Field of the Invention
[0003] This invention relates to systems, methods, and apparatus
for creating documents.
[0004] 2. Background and Relevant Art
[0005] In an information-based economy, written documents may be
central to many enterprises. Examples of such documents include
legal documents, medical reports, law-enforcement (e.g., police)
reports, legislative documents, regulatory documents, grant
solicitation documents, and grant proposal documents. As a result,
professionals in many fields may spend a significant portion of
time writing and editing various documents. Typically, documents
are reread and edited multiple times to achieve acceptable language
and structure in the document. The legal profession is one example
of a field where professionals may spend an inordinate amount of
time composing and editing written documents, such as contracts,
litigation documents, patents, and client letters.
[0006] Computers and/or computer systems may enable a drafter to
compose and edit documents. For example, the drafter may use word
processing software for generating documents. The drafter also may
use a document assembly system to create documents. A typical
document assembly system may allow the drafter to enter information
into a form. Subsequently, such a system may generate a document
using preset text blocks and/or a framework based on the
information in the information entered by the drafter. Although
such document assembly systems may improve the efficiency of
document creation processes, typical document assembly systems lack
flexibility to create customized documents, which may be desired by
the drafter.
BRIEF SUMMARY OF THE INVENTION
[0007] In one or more embodiments, the present invention provides a
document drafting system and methods that may facilitate reuse of
previously created text. The document drafting system may include
computer executable code executed on a general purpose or a special
purpose computer. In some instances, reusing previously created
text may improve drafting productivity. More specifically, the
document drafting system may reduce time required for a user to
formulate, enter, and/or proofread sentence segments, sentences,
paragraphs, entire documents, or combinations thereof. Furthermore,
the document drafting system may increase convenience and/or reduce
time required to locate a desired or suitable existing text.
[0008] One embodiment includes a computer system for assembling a
document. The computer system includes one or more processors, a
system memory, a display capable of providing information to a
user, the display controlled by the one or more processors, and one
or more computer-readable storage media having stored thereon
computer-executable instructions. When executed by the one or more
processors, the computer-executable instructions cause the computer
system to implement a method for assembling a document. The method
includes an act of receiving at least one word entry from the user
and an act of retrieving a plurality of relevant texts from stored
text at least partially based on the received at least one word
entry from the user. The method also includes an act of displaying
the relevant texts on the display and an act of receiving at least
one selection of the relevant text from the user. The method also
includes an act of adding the received at least one selection of
the relevant texts to a document.
[0009] Another embodiment includes a computer program product
comprising one or more computer-readable storage media having
stored thereon computer-executable instructions that, when executed
by one or more processors of a computer system, cause the computer
system to implement a method for assembling a document. The method
include an act of receiving at least one word entry from a user and
an act of retrieving a plurality of relevant texts from stored text
at least partially based on the received at least one word entry
from the user. The method also includes an act of displaying the
relevant texts on the display and an act of receiving at least one
selection of the relevant texts from the user. Moreover, the method
includes an act of adding the received at least one selection of
the relevant texts to a document.
[0010] Yet one other embodiment includes a method, implemented at a
computer system that includes one or more processors and system
memory, for assembling documents. The method includes an act of
receiving at least one word entry from a user and an act of
retrieving a plurality of relevant texts from stored text at least
partially based on the received at least one word entry from the
user. The method further includes an act of displaying the relevant
texts on the display and an act of receiving at least one selection
of the relevant texts from the user. The method also includes an
act of adding the received at least one selection of the relevant
texts to a document.
[0011] Additional features and advantages of exemplary
implementations of the invention will be set forth in the
description which follows, and in part will be obvious from the
description, or may be learned by the practice of such exemplary
implementations. The features and advantages of such
implementations may be realized and obtained by means of the
instruments and combinations particularly pointed out in the
appended claims. These and other features will become more fully
apparent from the following description and appended claims, or may
be learned by the practice of such exemplary implementations as set
forth hereinafter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] In order to describe the manner in which the above-recited
and other advantages and features of the invention may be obtained,
a more particular description of the invention briefly described
above will be rendered by reference to specific embodiments thereof
which are illustrated in the appended drawings. For better
understanding, the like elements have been designated by like
reference numbers throughout the various accompanying figures.
Understanding that these drawings depict only typical embodiments
of the invention and are not therefore to be considered to be
limiting of its scope, the invention will be described and
explained with additional specificity and detail through the use of
the accompanying drawings in which:
[0013] FIG. 1A illustrates a flowchart of a method of assembling a
document in accordance with one embodiment;
[0014] FIG. 1B illustrates a flowchart of a method of assembling a
document in accordance with another embodiment;
[0015] FIG. 2 illustrates a flowchart of a method of assembling a
document in accordance with yet another embodiment;
[0016] FIG. 3 illustrates a flowchart of a method of assembling a
document in accordance with yet another embodiment;
[0017] FIG. 4 illustrates a flowchart of a method of assembling a
document, in accordance with yet one other embodiment;
[0018] FIG. 5 illustrates a schematic of user interface for a
document assembly system, in accordance with one embodiment;
[0019] FIG. 6 illustrates a flowchart of a method of parsing in
accordance with one embodiment;
[0020] FIG. 7 illustrate a flowchart of a method of parsing in
accordance with another embodiment;
[0021] FIG. 8 illustrates a flowchart of a method of parsing in
accordance with yet one other embodiment;
[0022] FIG. 9 illustrates a block diagram of a document assembly
system, in accordance with one embodiment; and
[0023] FIG. 10 illustrates a block diagram of a computer system in
accordance with one embodiment.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0024] In one or more embodiments, the present invention provides a
document drafting system and methods that may facilitate reuse
previously created and/or existing text. The document drafting
system may include computer executable code executed on a general
purpose or a special purpose computer. In some instance, reusing
previously created text may improve drafting productivity. More
specifically, the document drafting system may reduce time required
for a user to formulate, enter, and/or proofread sentence segments,
sentences, paragraphs, entire documents, or combinations thereof.
Furthermore, the document drafting system may increase convenience
and/or reduce time required to locate a desired or suitable
existing text. As used herein, the term "document" refers to an
electronic document that has text.
[0025] The document drafting system also may enable generation of a
database containing text from previously created documents. For
instance, the document drafting system may parse existing documents
or text to create and/or update the database containing text. In
particular, the document drafting system may identify desirable
text segments, store and/or index such segments. Moreover, the
document drafting system may store one or more text segments in the
database containing text.
[0026] In some embodiments, during drafting, the document drafting
system may enable the user to query the database containing text
and may retrieve text therefrom. Additionally, the document
drafting system also may provide an integrated drafting
environment. For example, such an integrated drafting environment
may allow the user to query the database for desired text, receive
results of the query, select one or more of the received results,
add text from the selected results into a document, or perform one
or more combinations thereof. Thus, the document drafting system
may be used to draft a variety of documents, including but not
limited to legal documents, medical notes, reports, legislation,
administrative regulations, technical documents, news reports, etc.
Examples of legal documents include contracts, litigation
documents, patents, various transactional documents, etc.
[0027] As described above, the document drafting system may provide
the user with text in response to the user's one or more queries.
More specifically, in some embodiments, the document drafting
system may retrieve text in response to entries made by the user.
As used herein, the terms "entry" or "entries," as applicable,
refer to entries of one or more words made by the user. Operations
performed by a document drafting system, for example, may include
acts, as illustrated in a flowchart of FIG. 1A, that may be
executed by or on a computer system that may comprise one or more
processors. The acts of FIG. 1A, and others presented herein, may
be implemented while a user is writing a document, and may enable a
user to readily assemble a document by reusing preexisting text,
such as word combinations, clauses, sentences and/or paragraphs.
The preexisting text may have been previously drafted by the user
or by other writers. In this manner the user need not rewrite
preexisting text, and may readily include the desired preexisting
text(s) in one or more locations in his document.
[0028] The method may include the computer system receiving one or
more entries from the user (act 110). As described above, the user
may make such entries while creating a document. For instance, the
computer system may receive entries as the user enters text into
the document. The entries received by the computer system may
include entries the user makes while creating the document. For
example, in some embodiments, as further described below, the user
may type text into a word processor application (forming words,
sentence, fragments, sentences, etc.), which may be the entries
that the computer system receives from the user in act 110. The
term "word processor" refers to any program or software that allows
a user to create documents, edit documents, save documents, format
documents, or a combination thereof.
[0029] Additionally or alternatively, a user's speech may be
collected via a microphone, and speech recognition software may
transcribe the user's speech into text that may form words,
sentence fragments, sentences, etc., and which may be the entries
the computer system receives from the user in act 110. For example,
speech recognition software by Nuance Communication, Inc., such as
Nuance Dragon NaturallySpeaking.TM. speech recognition software,
may be employed to convert a user's spoken words to text, including
but not limited to text entered in applications such as word
processors, email applications, web browsers, etc. Furthermore, the
entry may include select text written by the user in the document
(e.g., the most recent written text or a selected fragment of the
written text, such as a specific number of words last entered by
the user). In one or more embodiments, the entry may be one or more
search terms. The search terms may be provided by the user outside
of a text document that the user may be drafting. For example, in
act 110, the computer system may receive entries made by the user
in a search line, as further described below. Furthermore, the
search line may be displayed to the user as part of the word
processor application and/or as part of a standalone system.
[0030] Accordingly, the entry or entries received from the user may
be search terms that, for example, may be used to query a database.
Such search term entries, as described above, may be the words
added to a documents (e.g., during creation thereof) or in a search
line, which may be outside of the document. For example, as the
user is creating the document, the user may add the following text
to the document: "`Change of Control` means the consummation of a
transaction in which any entity becomes . . . . " Any portion of
the entered text, as preset by the user and/or as may be determined
by the document drafting system, may be the entry received by the
computer system from the user, in act 110. In some embodiments, as
described above, the entry may be a preset number of words as
counted from a preset position in the document and in a preset. For
instance, the entry may comprise a certain number of words (e.g.,
five words, four words, three words, or two words), counted to the
left from a current position of the cursor in the document. It
should be noted, however, that the number of words, starting
position and direction of the count may be changed as desired by
the user and/or by the document drafting software, as further
discussed below.
[0031] Alternatively or additionally, in at least one embodiment,
the entries received from the user in act 110 may be commands. More
specifically, the entries may be commands that correspond to a
specific text that the user desires to add to a document. For
instance, the "command" type of entry may trigger the document
drafting system to retrieve relevant text, as further described
below, which is associated with the particular comment. As used
herein, the term "relevant text" refers to certain text retrieved
and/or provided by the document assembly system; such text may be
retrieved based on certain parameters and/or requirements defined
within the document assembly system (e.g., a query string used for
querying a database containing text).
[0032] Upon receiving the entry from the user, the computer system
may execute a text retrieval process (act 120), whereby the
computer system may retrieve relevant text from stored text in
response to the entry received from the user. In some embodiments,
the stored text is contained within a text repository, such as a
database. Thus, for example, the text retrieval process may include
querying the text repository (e.g., querying the database, such as
an SQL database).
[0033] The stored text also may comprise text stored in
non-volatile (e.g., storage devices such as hard disks, optical
discs, magnetic tape, flash devices) and/or volatile memory devices
(e.g., RAM). The stored text may include text from one or more
documents, which may be parsed therefrom and/or stored in the text
repository. The text retrieved during the text retrieval process of
act 120 may have been written, at least in, part by the user and/or
by others, for instance, as part of one or more documents. In some
embodiments, the stored text and/or the text retrieved during the
text retrieval process of act 120 may include text from a document
that is presently open, and which the user may be presently
drafting or editing. In some embodiments, the text retrieved during
the text retrieval process of act 120 may include text not created
by the user, which may be stored in one or more databases. Such
text may include text from public and/or private documents, for
example, legal documents (e.g., case documents), legislative
documents, regulatory documents, patents and patent applications,
financial filing documents (e.g., SEC filing documents), medical
and pharmaceutical texts, encyclopedic texts, news achieves, web
pages, etc.
[0034] In some embodiments, the stored text may be stored in a
database as text fragments, such as clauses, sentences, and/or
paragraphs. The text fragments, sentences, and/or paragraphs may be
tagged or identified with various identifying information, such as
one or more of sentence boundaries, named entity tags, parts of
speech tags, keywords, parse trees, dependency trees, words
relevant to the identified keywords (e.g., synonyms, which may be
obtained from WorldNet), and chunks and/or super-chunks of words. A
chunk is a portion of a sentence comprising several (e.g., two or
more, three or more, or four or more) words, and does not contain
all the words of the sentence. In some embodiments, a chunk is a
short phrase or a meaningful portion of a sentence. In some
embodiments, a chunk includes at least one verb (e.g., one or more,
two or more, or three or more). In some embodiments, a chunk
includes no more than one verb. In other embodiments, a chunk
includes no more than two verbs. Depending on user's preferences,
however, chunks may include more than one verb. The text fragments,
sentences, and/or paragraphs may (but do not have to) be stored in
a database (e.g., a relational database, such as Microsoft.RTM. SQL
Server Express database).
[0035] The text retrieval process that may be executed in act 120
may include one or more text search processes by which the computer
system searches the stored text and returns relevant text based on
the one or more entries (e.g., search terms such as one or more
words) from the user. The text retrieval process may include a
full-text search where all the words in the stored text are
examined so as to find relevant text. Alternatively or
additionally, the text retrieval process may utilize an index of
the stored text (e.g., where the index may include a list of
terms), which may have been created previously. The index or the
database may be searched during the text retrieval process so as to
retrieve the relevant text. Various search algorithms, which are
known to those skilled in the art, may be used to perform the
search of the stored text, including SQL querying, if the text is
stored in database.
[0036] In some embodiments, the text retrieval process includes a
search process that is performed on sentences only and/or for parts
of speech. Such a process may utilize stored text that has been
parsed at least partially based on sentence boundaries and/or parts
of speech (as described below for the method of FIG. 8). Search
results may be ranked higher if the search word is a particular
part of speech (e.g., a verb). Alternatively, or additionally,
search results may be ranked higher when search words appear in
conjunction with another in the same sentence.
[0037] The relevant text may comprise stored text that
substantially matches the one or more entries from the user.
Alternatively or additionally, the relevant text may comprise
stored text in a document that follows and/or precedes text that
substantially matches the one or more entries from the user. For
example, the relevant text may include text fragments, such as a
sentence or parts of sentence, which include substantially matching
text for the one or more entries from the user but also may include
additional text following or preceding the substantially matching
text. In some embodiments, a plurality of relevant texts may be
retrieved.
[0038] The plurality of retrieved relevant texts may be ranked
based on how closely the retrieved relevant texts include
substantially matching text for the one or more entries from the
user. For example, the results may be ranked based on the matching
of the number of words in an entry from the user and/or the
sequence of the words in an entry from the user. A highest rank may
be provided to relevant text that includes the most same words as
the entry from the user and/or most of the same words in a similar
sequence as the entry from the user.
[0039] Additionally, the relevant texts may be ranked based on most
commonly occurring word combinations (e.g., within the database
containing the stored text; within another corpus of parsed text).
For example, when the user provides search terms, such as words X1,
X2, and X3, the results may be ranked (and displayed in the order
of ranking) based on the most commonly occurring combination or
sequence of these words within a sentence or a chunk stored in the
database. Additionally or alternatively, the ranking may be based
on the most commonly occurring sequence of the search words within
another database (e.g., as noted above, a corpus of parsed text).
Various other ranking algorithms known to those skilled in the art
may be used to produce the desired rankings of the results.
[0040] In one or more embodiments, the computer system may compute
a readability metric and assign the same to the stored text. For
example, the readability metric for a particular sentence or chunk
may be calculated by comparing frequency of use of a particular
word sequence or sequences (e.g., particular verb-noun arrangement)
within such sentence or chunk with the average use within a corpus.
In some instances, the corpus may be the collective stored text.
Additionally or alternatively, the corpus may be other, parsed
corpus from one or more sources, such as newspapers, legal
documents, etc.
[0041] In some embodiments, relevance ranking of the relevant text
may at least in part be determined by a user's previous search
string and subsequent selections of the results, which may be
stored under a user's profile. The user profile may include
historical information, such as historical information relating to
the use of the document assembly system. For example, the
historical information may include information about relevant text
that the user has previously incorporated into other documents he
has drafted. More recent relevant text that the user has previously
incorporated into other documents may be given more weight in the
relevance ranking method. For instance, the historical profile may
include relationships between search terms and selected relevant
texts, search term sequences and corresponding sequences in the
selected relevant texts, types of documents corresponding to the
search terms (which were being created by the user during the
search and/or from which the user selected the relevant text),
etc.
[0042] The computer system may provide the retrieved relevant text
to the user (act 130). Providing the retrieved text to the user may
include presenting the retrieved text to the user. The retrieved
relevant text may be presented via a visual display. Alternatively
or additionally, the retrieved relevant text may be presented via
audio, such as speech that may be created via text-to-speech
computer processes. The retrieved relevant text may be presented as
a list of items, where the list may be arranged in any desired
order, and where the desired order may be specified by the user or
by the software or computer system, as previously defined. For
example, the desired order for the relevant texts may be in
descending or ascending relevance rank, as determined by the
ranking method. Alternatively or additionally, the desired order
for the relevant texts may be in descending or ascending dates of
creation or last modification. Alternatively or additionally, the
desired order for the relevant texts may be based on the author's
name and/or organizational affiliation of the relevant texts, such
as in ascending or descending alphabetical order of the author's
name and/or organizational affiliation.
[0043] In some embodiments, the presented relevant text to the user
and a document that is presently being drafted are viewable
simultaneously. As described in more detail below, the presented
relevant text and the document may be displayed simultaneously via
a split-screen display. Furthermore, the document assembly system
may update the relevant text presented to the user, while the user
drafts the document. In particular, as described below, the
document assembly system may obtain a desired or predetermined
number of words entered or selected by the user during the drafting
process and may use such words as search terms for obtaining the
relevant text.
[0044] The user may select one or more of the presented relevant
texts. The user may select text by moving a cursor (e.g., via an
cursor control device, such as a mouse, touchpad, touch display)
over the text and selecting the text via a specified text-selection
process (e.g., menu button and/or a cursor control device button),
such as clicking one or more times on a cursor control device
button. In some embodiments, the user may select the relevant text
by highlighting a portion of presented text. Additionally or
alternatively, the user may drag-and-drop the relevant text (as
part of the selection process). Such dragging and dropping may be
achieve with the aid of a number of input devices, such as a mouse,
a keyboard, a touch screen, a microphone (for speech activated
commands), and a combination thereof. Thus, the computer system may
receive the selection of the relevant text in act 140.
[0045] The user may then provide an indication that he wants to add
the selected relevant text to a document, for example, to an open
document that he may be drafting. The user may choose to add the
selected text to a selected document at a selected location in the
document. In some embodiments, the selected location to add the
selected text may the location of a cursor, such as the cursor in a
word processing environment for a presently open document. In
response, the computer system may add the selected relevant text to
the selected document (act 150), such as a document that is
currently being drafted and/or may be open. Once the text is added
to the document, the process may be repeated when/if the user
provides an additional entry (acts 160 and decision point 170).
[0046] As described above, the relevant text may be presented to
the user as the user is drafting the document. For instance, as
illustrated in FIG. 1B, the document assembly system may receive
entry from the user (act 110a) and may subsequently check whether a
minimum number of entries have been received in act 112. If the
minimum number of entries has been received from the user, the
document assembly system may proceed in a similar manner as
described above in connection with FIG. 1A. Namely, the document
assembly system may execute text retrieval process (act 120) and
may provide the relevant text to the user (act 130). Additionally,
the document assembly system also may receive selection of relevant
text (act 140) and may add the selected relevant text in the act
150.
[0047] As described above, in some embodiments, the search process
or retrieval of relevant text may commence only when the document
assembly system has received the minimum number of entries from the
user. For example, if the minimum number is four (4), once the user
has entered four words, the document assembly system will proceed
to retrieve relevant text. Additionally or alternatively, as the
user makes additional entries (e.g., types new words in the
document; speaks new words to a speech recognition system) the
document assembly system may check for additional entries from the
user in act 160 (and decision point 170) and may receive additional
entries from the user in act 110b. Furthermore, the document
assembly system may incorporate an upper limit on the number of
entries used for retrieving relevant text (e.g., in a search string
or a query). For instance, the document assembly system may check
whether the received number of entries has reached a maximum number
of entries in act 180. If the maximum number of entries has not
been reached, the document assembly may proceed to execute text
retrieval process (act 120). Alternatively, if the maximum number
of entries has been reached, the document assembly system may limit
the search string (or generally the number of entries used for
retrieving text) in act 190 and may subsequently execute text
retrieval process (act 120).
[0048] The minimum and/or maximum number of entries may be
predetermined (e.g., fixed by the user or within the document
assembly system) or may be defined by an algorithm. For instance,
the minimum and/or maximum number of entries may be static
number(s), for example, chosen by the user. Additionally or
alternatively, the minimum and/or maximum number of entries may be
determined by the document assembly system based on one or more
parameters; for instance, the minimum and/or maximum number of
entries may be at least partially based on the load on the database
storing text, and/or data transfer rate.
[0049] Additionally, it should be noted that the document assembly
system may execute all or some of the acts identified herein.
Accordingly, the document assembly system may incorporate an upper
and/or a lower limit for the number of entries used in the text
retrieval process. Thus, for example, as the user enters text
(e.g., types or speaks words), the document assembly system may
select a minimum and/or maximum number of words from the entered
text (e.g., in the line preceding the cursor) to use in the text
retrieval process (of act 120). Thus, the relevant text provided by
the document assembly system in act 130 may be updated based on the
retrieved results, which may be at least partially based on the
number of words used to execute the text retrieval process in act
120 (e.g., number of words used in the search string or query).
[0050] FIG. 2 is a flowchart of acts for assembling a document that
may be performed by the document assembly system in accordance with
one embodiment of the present inventions, as may be implemented by
a computer system that may comprise one or more processors. The
document assembly system may perform an act of receiving one or
more search terms from a user (act 210).
[0051] In one embodiment, a search prompt is presented to the user,
and the user may enter one or more search terms in the search
prompt. The search prompt may be a line visible on an interface
(e.g., a display) of the computer system as a box in which the user
may enter search terms. Additionally or alternatively, the search
prompt may be invisible to the user--for example, the search terms
may be entered as speech commands recognized by speech recognition
software.
[0052] The search terms may include one or more words. Additionally
or alternatively, the search terms may include one or more word
sequences (i.e., a collection of words in a specific order), as may
be indicated by the user entering predetermined marks (e.g.,
quotation marks) at the beginning and end of a word sequence as
well as Boolean terms designating relative position and/or presence
of text segments (such as words or word combinations) in the
searched/stored text. In some embodiments, the user may specify
whether the relevant text may include other words in-between the
words of the entered word sequence, and/or whether the retrieved
text should include only the words of the entered word sequence
with no other intervening words. The user may be provided the
option to specify whether word stemming and/or synonyms should be
utilized for the entered search terms.
[0053] Upon receiving the search terms from the user, the computer
system may execute a text retrieval process (act 220), as described
for act 120 above. The computer system may provide (e.g., present)
the relevant text to the user (act 230), as described for act 130
above. The user may select one or more of the presented relevant
texts, and the computer system may receive the selection of the
relevant text (act 240), as described for act 140 above.
[0054] The user may then provide an indication that he wants to add
the selected relevant text to a document, such as an open document
that he may be drafting. The user may provide an indication to add
the selected text to a selected document at a selected location in
the document, and the computer system may receive the selected
location in the document (act 250). In some embodiments, the
selected location to add the selected text may be the location of a
cursor, such as the cursor in a word processing environment for a
presently open document. In response, the computer system may add
the selected relevant text to the selected document (act 260), such
as a document that is currently being drafted and/or may be open.
Once the text is added to the document, the process may repeat when
the user provides an additional entry (acts 270, 280).
[0055] In some embodiments, the text retrieval process may be
trained (act 290). The training of the text retrieval process may
be performed at least partially based on the selection of the
relevant text by the user. Training of the text retrieval process
may include updating a user profile that may include selection
frequency weightings for previously selected relevant texts and
corresponding search terms and/or search strings used. The
selection frequency weightings associated with specific relevant
texts may increase with an increasing frequency of user selections
and additions of the specific relevant texts to documents.
Presented relevant texts may be at least partially ranked based on
the selection frequency weightings in the user profile and may be
presented to the user in decreasing or increasing ranking order, as
may be performed in act 230.
[0056] FIG. 3 is a flowchart of acts performed by the document
assembly system in accordance with at least one embodiment, in
assembling a document, as may be implemented by a computer system
that may comprise one or more processors. The document assembly
system may provide for the search and presentation of relevant text
at least partially based on the text in an open document that the
user is drafting. The search and/or presentation of the relevant
text to a user may be performed as the user writes (e.g., types or
creates via speech-to-text input or other means of input) the
document without the user being required to enter search terms. The
search and/or presentation of relevant text to the user may be
performed repetitively in response to the writing of text (e.g.,
words or word combinations) most recently provided by the user in
the document. In this manner, a user may view and/or select
relevant text that he wishes to incorporate into the document he is
writing.
[0057] The method shown in FIG. 3 may comprise receiving text
entered by a user (act 310), whereby the text may be a portion
(e.g., a word or word combination) of the document being drafted.
The text may be the most recent portion of the document being
drafted, such as a number of words that have most recently been
written by the user. The number of words may be specified by the
user and/or may be a predefined parameter (e.g., as may be set by a
configuration process and/or file). In some embodiments, the text
received in act 310 may be one or more words in the document being
drafted that the user may select, such as by highlighting text
(e.g., using a cursor).
[0058] Upon receiving the text entered by the user, the computer
system may execute a generic text generation process (act 320)
using the text entered by the user as input. The generic text
generation process may include utilizing a named entity recognition
process to identify named entities in the received text, using
methods for named entity recognition known by those of skill in the
art. Named entities may include proper names (e.g., of people,
organizations, nations, states, cities), dates and times. The
generic text generation process may then generate generic text
search string 330 by removing at least one of the named entities
from the text entered by the user. In some embodiments, all
identified named entities are removed to generate generic text.
[0059] The generic text search string may then be used to obtain
relevant text from stored text. For example, the generic text
search string may be used to search a database of stored text.
Search terms may be generated from the generic text, wherein the
computer system may execute a search terms generation process (act
340) that may generate search terms 350. In one embodiment, the
search terms generation process may include identifying parts of
speech, identifying synonyms, generating a parse tree, and/or
generating a dependency tree from the generic text and using one or
more of these identifiers to search for relevant text.
[0060] The computer system may then execute a text retrieval
process using the search terms (act 360), as described for act 120
above. In some embodiments, the search terms used to execute the
text retrieval process are viewable by the user. In other words,
the entry that is provided to the computer system and subsequently
used to retrieve relevant text may be displayed by the computer
system to the user. Hence, in the instance where the entry is text
entered by the user in a document (e.g., wherein the entry is a
predetermined number of words entered last), the computer system
may display such entry, so the user may immediately know which
words are being used as the entry for retrieving relevant text. The
computer system may provide (e.g., present) the relevant text to
the user (act 370), as described for act 130 above. The search
terms used to execute the text retrieval process may be presented
in conjunction with the relevant text, such as in a common window.
The user may select one or more of the provided relevant texts, and
the computer system may receive the selection of the relevant text
(act 380), as described for act 140 above.
[0061] The computer system also may give the user a choice of one
or more databases (containing stored text) to query for relevant
text. Such databases may be located on and/or connected to one or
more computers and may be connected together through a network.
Additionally, the computer system may allow the user to query
databases, indexes, and other storage mechanisms that do not
contain stored text (as used herein). For instance, the user may
direct the computer system to submit the entry (e.g., latest string
or words entered in a document) to an Internet search engine, such
as Google, Bing, Yahoo, or other search engines. Accordingly, in
addition to providing the user with relevant text, in response to
the entries provided by the user, the computer system also may
submit the user's entry to an Internet search engine and provide
(e.g., display) search result produced or retrieved by the Internet
search engine. Similarly, the entry also may be submitted to other
search facilities and/or searchable databases by the computer
system. Likewise, results obtained or received from such search
facilities and/or searchable database also may be provided to the
user.
[0062] The user may provide an indication of a location in the
document where the selected relevant text should be added, and the
computer system may receive this information (act 390), as was
previously described for act 250 above. The computer system may add
the selected relevant text to the selected location in the document
(act 400), as was previously described for act 260 above. Once the
text is added to the document, the process may repeat when the user
enters additional text in the document (acts 450 and 460), and as
such the presentation of the relevant text to the user may be
performed repetitively (e.g., after every three or more
user-entered words, after every five or more user-entered words,
after every ten or more user-entered words) in response to text
most recently entered by the user in the document.
[0063] One or more other optional processes may be performed, which
may enhance the performance of the document assembly system. When
information from one of such processes is not used by another, two
or more of these processes may be performed in parallel.
Alternatively, such processes may be performed sequentially, or as
a combination of parallel and sequential processes. One such
optional process is text retrieval training process (act 410),
which was previously described for act 290 above. The computer
system may perform the text retrieval process after receiving the
selection of a location in the document (act 390) or after the text
is added to the selected location in the document (act 400).
Another such optional process may also include the training of the
search terms generation process (act 420). The training may be at
least partially based on the frequency of word or word sequence
usage within the stored text and/or may be based on search terms
used and subsequent selection(s) made by a specific user. In some
embodiments, specific search term(s) may be correlated with a
specific subsequent selection, which may be ranked higher in
subsequent search results in response to the same or similar search
terms entered by the same (and/or by other) user(s).
[0064] Other optional processes may be related to enhancing the
quality (e.g., usefulness or level of relevancy) of the relevant
text provided to the user. Such processes may include training
processes that may improve any named entity recognition processes
that may be used by the document assembly and associated methods.
In particular, the document assembly system may train search terms
generation process (act 420). For instance, if a named entity
recognition process is employed to present relevant text to the
user that is a generic version of some stored text (e.g., absent
named entities), and some named entities are not identified by the
process, the user may choose to modify (e.g., delete and/or
replace) any remaining named entities in the selected text so as to
suit their particular situation. Additionally or alternatively, the
document assembly system may receive modifications of selected
relevant text from the user (act 430), which, for example, may
include an indication by the user that the modified text is one or
more named entities. In some embodiments, the document assembly
system may present a user interface, such as a menu, with one or
more options associated with named entity training. The user might
be provided with the option to highlight named entities in the
selected relevant text and then select a named entity training
option (e.g., in the menu). The named entity recognition process
may then be trained to identify the missed named entities (act
440), as is known by those of ordinary skill in the art. The
training process enables the named entity recognition process to
improve with use and with input from one or more users.
[0065] FIG. 4 is a flowchart of acts performed by the document
assembly system, in accordance with one embodiment of the
invention, for assembling a document, as may be implemented by a
computer system that may comprise one or more processors. In some
embodiments, the document assembly system may identify one or more
named entities in a first text, and add a generic portion of the
first text into a document, wherein the generic portion is absent
at least one of the named entities (e.g., all of the identified
named entities).
[0066] First text 460 provided to the computer system may be text
from an existing document. In some embodiments, the first text 460
may be part of a database. The computer system may proceed to
identify named entities in the first text (act 470), as may be
achieved using named entity recognition processes. The computer
system may proceed to generate a generic portion 490 of the first
text, by removing at least one of the identified names entities
(e.g., all of the identified named entities) from the first text
(act 480).
[0067] A document may be assembled by adding the generic portion
490 of the first text into a document 510 (act 500), so as to
create a document 520 including the generic portion of the first
text. In some embodiments, document 510 may be a document that is
being drafted by a user. The user may provide a selection, to the
computer system, of at least a portion of the first text 460 to add
to document 510. The computer system may thus receive the selection
of at least one portion of the first text from the user, and the
addition of the generic portion of the first text into the document
may be performed by the computer system, at least in part, in
response to the user's selection from the first text.
[0068] In some embodiments, the computer system may be further
programmed to incorporate one or more replacement named entities
into the document with the generic portion of the first text that
is added to the document. The computer system may utilize a mapping
between the one or more named entities in the first text and the
one or more replacement named entities so as to incorporate the one
or more replacement named entities into the document with the
generic portion of the first text that is added to the document.
The mapping between the one or more named entities and the one or
more replacement name entities may be determined, at least in part,
based on information provided by the user. In one embodiment, a
mapping may be provided by named entity variables specified for the
document being drafted. For example, in the case of legal
documents, some typical named entity variables may include the
defendant and the plaintiff names and places of residence. In
another example, in the case of clinical medical notes, some
typical named entity variables may include the patient's name and
date of examination. Although specific document examples are
provided above, it should be appreciated that the methods described
herein may be utilized for any type of document, including but not
limited to legal and/or medical notes.
[0069] FIG. 5 is a schematic of user interface for a document
assembly system. In some embodiments, the user interface may be
such that presented relevant text and the document being written
are simultaneously viewable by the user. The user interface of the
document assembly system may include a word processing window 530
and a relevant text window 540 that may be viewable simultaneously
by the user. Word processing window 530 and relevant text window
540 may be generated by separate processes or by the same process.
Word processing window 530 and relevant text window 540 may be
daughter windows in a parent window (not shown) that may be
generated by one or more processes.
[0070] In one embodiment, word processing window 530 may be
generated by a word processing application, such as Microsoft.RTM.
Word word processor. Relevant text window 540 may be generated by a
separate application that may interface with the word processing
application; for example, the separate application may interface
with the running session of Microsoft.RTM. Word with the use of
Visual Basic for Applications (VBA). In some embodiments, relevant
text window 540 may be generated by an add-on to a word processing
application that generates word processing window 530. Such an
add-on for the Microsoft.RTM. Word word processor may be developed
using VSTO (Visual Studio Tools for Office).
[0071] Word processing window 530 may include a document viewing
field 550, in which the document text being drafted 560 is
presented to the user and in which the user may enter additional
text at the location of cursor 590. Word processing window 530 may
include menu bar 570 that enables the user to manipulate the
document (e.g., document saving/opening, document editing,
formatting, etc.). In addition, word processing window 530 may
include one or more status indicators, such as status line 580 that
may be used to display information about the document being
drafted, including but not limited to the document name and/or
location.
[0072] Relevant text window 540 may include document type field 600
that enables the user to select the type of document he is
drafting. The search and hence the relevant text presented to the
user may be restricted to search results from a document database
of the specified type of document. Relevant text window 540 may
include auto-search selectors (e.g., off button 610 and on button
620) that allow a user to specify whether the search and hence the
relevant text should be presented automatically in response to the
user drafting the document text, as previously described. Search
terms field 630 provides a location for the user to enter search
terms and execute a search based on those entered search terms.
Relevant text results field 640 provides a location for relevant
text results 650 and 660 to be presented to the user.
[0073] FIG. 6 is a flowchart of acts that may be performed by the
document assembly system in accordance with at least one
embodiment, which may also parse text, as may be implemented by a
computer system that may comprise one or more processors. The
method may be implemented by a document assembly system that may
implement document assembly methods, such as the methods previously
described in the associated text of FIGS. 1 to 4. The parsed text
may be used to form a database of text fragments that may be
utilized by the text retrieval processes of the document assembly
system, such as text retrieval processes 120, 220, and/or 360.
[0074] The document assembly system may provide selected stored
text (act 670) to the computer system, as may be selected by a
user. The selection of the stored text may be provided by a user
via a user interface (e.g., of a document assembly system), by a
configuration file (e.g., that may be accessed by a document
assembly system), or by any other suitable technique. For example,
a user may select a collection of documents (e.g., one or more
documents) stored on one or more storage systems. The stored text
may comprise text stored in non-volatile (e.g., storage devices
such as hard disks, optical discs, magnetic tape, flash devices)
and/or volatile memory devices (e.g., RAM).
[0075] The stored text may include text from one or more documents,
where the text may have been written at least in part by the user
and/or by others. In some embodiments, the stored text may include
text from a document that is presently open and which the user may
be presently drafting or editing. In some embodiments, the stored
text may include text from one or more documents that are presently
not open. In some embodiments, the stored text is stored directly
as text characters, thereby not requiring a text extraction
process.
[0076] The computer system may execute a text parsing process (act
680) on the selected stored text and generate parsed text 690.
Parsed text 690 may be stored in a database, such as SQL Server
database, which is used in the preferred embodiment. Hence, parsed
text may be stored text, as the term used herein.
[0077] In one embodiment, the text parsing process may begin with
the conversion of the contents of a document being parsed from the
format in which the document is stored (e.g., RTF, DOCX) into plain
text. A subsequent step may include the separation of the text into
a plurality of sentences utilizing one or more sentence boundary
disambiguation methods. In some embodiments, one or more sentences
(e.g., all sentences) of the plurality of sentences in the document
may be subjected to tree-parsing utilizing entropy-based techniques
commonly used in natural language processing (NLP) algorithms.
Tree-parsing may result in obtaining (e.g., for one or more
sentences, possibly all sentences) a set of text chucks, as
previously described. In some embodiments, text chucks may be
subjected to further processing, which may include identifying
parts of speech (POS), identifying words that may serve as
keywords, and/or computing various metrics that may facilitate the
ranking of the search results.
[0078] In some embodiments, the document parsing process may
include clustering. Clustering may include computing a
characteristic value (e.g., integer type value) for each text chunk
that is at least partially associated with the keyword composition
of the chunk, for example utilizing hashing algorithms. When text
chunks are merged in a database (e.g., a relational database) the
characteristic value may serve as a clustering metric that allows
similar chunks to be grouped. Such clustering is intended to
facilitate and speed-up the search process for large databases. In
some embodiments, association of text chunks with keywords, their
storage in the database, and/or updating of the respective indexing
structures may also be part of the parsing process for a given
document.
[0079] In other embodiments, clustering may be performed based on
other parameters or metrics. Paragraphs, sentence sequences,
sentences, sentence chunks, or combinations thereof may be
clustered based on similarities therebetween. For example, chunks
that have a predetermined number or percentage of the same (or
similar) words may be clustered together. Hence, for instance,
during parsing of documents, the computer system may determine
whether the chunks contain the same or similar words, the
percentage of such words, and whether such chunks should be
clustered together. The computer system also may calculate a metric
(such as an integer) that may represent a particular arrangement of
parts of speech within a chunk. Moreover, the integer computation,
such as hashing, may include removal of certain parts of speech
(e.g., articles) and subsequently computing the hash integer.
Furthermore, the computer system may change one or more words to a
predetermined form (e.g., change words from plural to singular) and
may subsequently compute the hash integer, which may be used for
clustering the chunks, sentences, etc.
[0080] FIG. 7 is a flowchart of acts that may be performed by the
document assembly system in accordance with one or more
embodiments, which may include parsing text, as may be implemented
by a computer system that may comprise one or more processors. The
method may be implemented by a document assembly system that may
implement document assembly methods, such as the methods previously
described in the associated text of FIGS. 1 to 4. The parsed text
may be used to form a database of text fragments that may be
utilized by the text retrieval processes of a document assembly
system, such as text retrieval processes 120, 220, and/or 360.
[0081] The method may include the computer system receiving one or
more locations of stored text (act 700). The one or more locations
of stored text may include, but is not limited to, the locations of
one more file folder(s) and/or one or more file archives (e.g.,
compressed file achieves). Documents within the file folders and/or
file archives may include encoded stored text that will be
extracted and parsed by the computer system.
[0082] The computer system may execute a text extraction process on
the stored text (act 710). The extraction process may include
generating extracted text 720 from stored text by using suitable
data decoding methods for the encoded stored text. For example, the
text extraction process may include converting one or more
Microsoft Office Binary files (.DOC), Open Office XML files, and/or
a PDF files to text. In some embodiments, the text extraction
process may include de-compressing compressed text data.
[0083] The computer system may then execute a text parsing process
(act 730) on the extracted text (act 720) so as to generate parsed
text 740, as previously described for text parsing process 680 of
the previous method.
[0084] FIG. 8 is a flowchart of acts performed by the document
assembly system in accordance with one embodiment, which may
include parsing text, as may be implemented by a computer system
that may comprise one or more processors. The method may be
implemented by a document assembly system that may implement
document assembly methods, such as the methods previously described
in the associated text of FIGS. 1 to 4. The parsed text may be used
to form a database of text fragments that may be utilized by the
text retrieval processes of a document assembly system, such as
text retrieval processes 120, 220, and/or 360.
[0085] The method may include a computer system receiving one or
more segments or chains of unparsed text (act 750), such as a
sentence segment, a sentence, a paragraph, multiple paragraphs, or
other general text. The unparsed text may be stored on a
computer-readable media, prior and subsequent to the parsing
process. For example, the unparsed text may be stored in document
files accessible by a word processing application, such as
Microsoft.RTM. Word document files, which may be stored on a
computer-readable media, such as an internal hard drive.
[0086] The method may include a computer system identifying
sentence boundaries (act 760), which demarcates the beginning and
end of sentences. There are numerous methods known to those of
ordinary skill in the art, which may be utilized to identify
sentence boundaries, for all or some of the sentences in a text,
which may (but does not have to be) the received unparsed text
(from act 750). For example, sentence boundary demarcation
algorithms used in the Open NLP project
(http://incubator.apache.org/opennlp/) or Sharp NLP project
(http://sharpnlp.codeplex.com/) may be used to determine the start
and end of a sentence.
[0087] The method may include a computer system identifying named
entities in the identified sentences (act 770). There are various
algorithms known to those of ordinary skill in the art that may be
used to determine the named entities in a sentence. For example, an
algorithm utilized by the mentioned Open NLP suite may be used to
identify named entities in a sentence. A text may (but does not
have to) be a parsed text, with identified sentence boundaries.
[0088] The method may include a computer system identifying parts
of speech for sentences (act 780). There are various algorithms
that may be used to identify parts of speech within a sentence,
which are known to those of ordinary skill in the art. For example,
an algorithm utilized by the mentioned Open NLP suite may be used
to identify the parts of speech.
[0089] The method may also include a computer system generating a
parse tree for sentences (act 790). Similarly, there are various
algorithms known to those of ordinary skill in the art, which may
be used to generate parse trees for sentences. The method may also
include a computer system generating dependency trees for sentences
(act 800).
[0090] The method may include a computer system identifying
sentence chunks and/or super-chunks (act 810). The chunks and
super-chunks may be formed of various numbers of words and may
comprise one or more verbs in combination with other parts of
speech, as may be defined by the chunk generating algorithm(s)
and/or, if/where permitted by the algorithm, as defined by a user.
For example, an algorithm utilized by the previously mentioned Open
NLP suite may be used to generate chunks.
[0091] The method may include a computer system identifying
keywords in a sentence (act 820). There are various methods for
designating keywords in a sentence, which are known to those of
ordinary skill in the art. The method may be rule-based and/or may
designate specific words or word types (e.g., part of speech, named
entities, etc.) as keywords. Similarly, the method may designate
specific words or word types to be excluded from keywords.
[0092] The method may include a computer system identifying words
that are related to the keywords (act 830). The computer system may
identify synonym words that may be used in conjunction with or in
lieu of the keywords. For example, for the word car a synonymous
word automobile may be identified; similarly, related words (more
specific and/or more general than the keyword), such as Ford or
vehicle or SUV, may be identified by the computer system.
[0093] The method may include a computer system storing the parsed
text as well as identifying values (act 840). Identifying values
may be, for example, the parameters identifying the beginning and
ending of a sentence. The text and corresponding identifying values
may be stored in a database, for example an SQL database, on any
computer-readable media.
[0094] The method may include a computer system checking for
availability of additional unparsed text after the received
unparsed text has been parsed by the one or more of the parsing
processes identified in the method of FIG. 8 (act 850). The method
may actively search for additional unparsed text on a designated
computer-readable media or may standby to receive additional
unparsed text, as identified by a user. If the method receives an
indication that there is additional unparsed text, whether from a
user or after locating the same, it may commence the process of
receiving the unparsed text (act 750) and may subsequently parse
the unparsed text.
[0095] For one or more of the methods described herein, such as the
methods described above (e.g., one or more of the methods
illustrated in the flowcharts of FIGS. 1-4 and 5-8), one or more of
the acts of the method may be performed automatically by the
computer system, without requiring user input. In some embodiments,
all of the acts of the method (e.g., one or more of the methods
illustrated in the flowcharts of FIGS. 1-4 and 5-8) may be
performed automatically by the computer system, without requiring
user input.
[0096] FIG. 9 is a block diagram of an illustrative embodiment of a
document assembly system, as may be implemented by a computer
system that may comprise one or more processors. The document
assembly system may include a word processor application 860, a
parser 870, a search engine 880, and/or a scheduled service agent
890. Parser 870 may translate documents (e.g., saved document 865)
to a plain text format, identify sentence boundaries, tree-parse
sentences, identify parts-of-speech, identify keywords, compute
metrics, cluster text chunks, index text, and/or store parsed text.
Scheduled service agent 890 may initiate the parsing of new
documents at scheduled times and/or dates, and/or at least
partially based on a detection of a number and/or total size of new
documents that have not yet been parsed. During operation of word
processor 860, a user may be presented relevant search results from
stored text 875 (e.g., in a database, such as a relational
database), and that selected portions of the search results 884 may
be added to the document being edited 886 in response to the user's
instructions.
[0097] FIG. 10 is a block diagram of an illustrative embodiment of
a general computer system 900 in accordance with at least one
embodiment of the present disclosure. Computer system 900 includes
a set of instructions that may be executed to cause computer system
900 to perform any one or more of the methods (or parts of one or
more of the methods) or computer based functions disclosed herein.
Computer system 900 may operate as a standalone device or may be
connected via a network to other computer systems or peripheral
devices.
[0098] In a networked deployment, computer system 900 operates in
the capacity of a server or as a client computer in a server-client
network environment, or as a peer computer system in a peer-to-peer
(or distributed) network environment. Computer system 900 may also
be implemented as or incorporated into various devices, such as a
personal computer (PC), a tablet PC, a set-top box, a personal
digital assistant (PDA), a mobile device, a palmtop computer, a
laptop computer, a desktop computer, a communications device, a
wireless telephone, a land-line telephone, a control system, a
camera, a smayner, a facsimile machine, a printer, a pager, a
personal trusted device, a web appliance, a network router, switch
or bridge, or any other machine capable of executing a set of
instructions (sequential or otherwise) that specify actions to be
taken by that machine. In a particular embodiment, computer system
900 is implemented using electronic devices that provide voice,
video or data communication. Further, while computer system 900 is
illustrated as a single system, the term "system" shall also be
taken to include any collection of systems or sub-systems that
individually or jointly execute a set, or multiple sets, of
instructions to perform one or more computer functions.
[0099] Computer system 900 includes a processor 902 such as a
central processing unit (CPU), a graphics processing unit (GPU), or
both. Moreover, computer system 900 includes a main memory 904 and
a static memory 906 that communicate with each other via a bus 908.
Computer system 900 further includes a display unit 910, such as a
liquid crystal display (LCD), an organic light emitting diode
(OLED), a flat panel display, a solid state display, or a cathode
ray tube (CRT). It should be noted that the display unit 910 may
comprise a single display or monitor or multiple displays or
monitors. Additionally, computer system 900 includes an input
device 912, such as a keyboard, and a cursor control device 914,
such as a mouse. Computer system 900 also includes a disk drive
unit 916, a signal generation device 918, such as a speaker or
remote control, and a network interface device 920.
[0100] A "network" is defined as one or more data links that enable
the transport of electronic data between computer, computer systems
and/or modules, and/or other electronic devices as well as any
combination thereof. When information is transferred or provided
over a network or another communications connection (either
hardwired, wireless, or a combination of hardwired or wireless) to
a computer, the computer properly views the connection as a
transmission medium. Transmissions media can include a network
and/or data links which can be used to carry desired program code
means in the form of computer-executable instructions or data
structures and which can be accessed by a general purpose or
special purpose computer. Combinations of the above should also be
included within the scope of computer-readable media.
[0101] In some embodiments, disk drive unit 916 includes a
computer-readable medium 922 in which one or more sets of
instructions 924 are embedded. Instructions 924 embody one or more
of the methods or logic as described herein. In a particular
embodiment, instructions 924 reside completely, or at least
partially, within main memory 904, static memory 906, and/or within
processor 902 during execution by computer system 900. Main memory
904 and processor 902 also include computer-readable media. Network
interface device 920 provides connectivity to a network 926 such as
a wide area network (WAN), a local area network (LAN), or other
network. The present disclosure contemplates a computer-readable
medium that includes instructions 924 or receives and executes
instructions 924 responsive to a propagated signal, so that a
device connected to network 926 may communicate voice, video or
data over network 926. Further, instructions 924 may be transmitted
or received by network 926 via network interface device 920.
[0102] In some embodiments, dedicated hardware implementations such
as application specific integrated circuits, programmable logic
arrays and other hardware devices may be constructed to implement
one or more of the methods described herein. Applications that
include the apparatus and systems of various embodiments may
broadly include a variety of electronic and computer systems. One
or more embodiments described herein may implement functions using
two or more specific interconnected hardware modules or devices
with related control and data signals that may be communicated
between and through the modules, or as portions of an
application-specific integrated circuit. Accordingly, the present
system encompasses software, firmware, or hardware implementations,
or a combination thereof.
[0103] In accordance with various embodiments of the present
disclosure, the methods described herein are implemented by
software code executable by a computer system (i.e., the computer
system may include computer-executable instructions that perform
various acts described herein). Further, in an exemplary,
non-limited embodiment, implementations may include distributed
processing, component/object distributed processing, and parallel
processing. Alternatively, virtual computer system processing may
be constructed to implement one or more of the methods or
functionality as described herein.
[0104] Computer-executable instructions comprise, for example,
instructions and data which, when executed at a processor, cause a
general purpose computer, special purpose computer, or special
purpose processing device to perform a certain function or group or
series of functions. The computer executable instructions may be,
for example, binaries, intermediate format instructions such as
assembly language, or source code. Although the subject matter has
been described in language specific to structural features and/or
methodological acts, it is to be understood that the subject matter
defined in the claims is not necessarily limited to the specific
embodiment, features, or acts described above. In other words, the
embodiments, features, and acts are disclosed as examples of
implementing the claims.
[0105] Those skilled in the art will appreciate that the invention
may be practiced in network computing environments with many types
of computer system configurations, including, personal computers,
desktop computers, laptop computers, message processors, hand-held
devices, multi-processor systems, microprocessor-based or
programmable consumer electronics, network PCs, minicomputers,
mainframe computers, mobile telephones, routers, switches, and the
like. Accordingly, the computer system may include multiple
computers connected over the network. Furthermore, any one of the
multiple computers comprising the computer system can perform any
number of the acts described herein. Hence, one or more acts may be
performed on a computer being utilized by the user and one or more
acts may be performed by another computer, connected (e.g., via a
network) to the computer being utilized by the user--together, the
computers may comprise the computer system performing the acts
described herein. In other words, the invention may also be
practiced in distributed system environments where local and remote
computer systems, which are linked (either by hardwired data links,
wireless data links, or by a combination of hardwired and wireless
data links) through a network, both perform tasks. In a distributed
system environment, program modules may be located in both local
and remote memory storage devices.
[0106] While the computer-readable medium is shown to be a single
medium, the term "computer-readable medium" includes a single
medium or multiple media, such as a centralized or distributed
database, and/or associated caches and servers that store one or
more sets of instructions. The term "computer-readable medium"
shall also include any medium that is capable of storing, encoding
or carrying a set of instructions for execution by a processor or
that cause a computer system to perform any one or more of the
methods or operations disclosed herein.
[0107] In a particular non-limiting, exemplary embodiment, the
computer-readable medium may include a solid-state memory such as a
memory card or other package that houses one or more non-volatile
read-only memories. Further, the computer-readable medium may be a
random access memory or other volatile re-writable memory.
Additionally, the computer-readable medium may include a
magneto-optical or optical medium, such as a disk or tapes or other
storage device to capture carrier wave signals such as a signal
communicated over a transmission medium. A digital file attachment
to an e-mail or other self-contained information archive or set of
archives may be considered a distribution medium that is equivalent
to a tangible storage medium. Accordingly, the disclosure is
considered to include any one or more of a computer-readable medium
or a distribution medium and other equivalents and successor media,
in which data or instructions may be stored.
[0108] In some embodiments, the computer system may be used for
reusing or recycling previously created text. Such text may be
previously created by one or more users or by a third party. For
instance, the computer system may parse previously created legal
documents and store parsed text therefrom (e.g., create stored
text). As the user is creating a particular document, and more
specifically, as the user types words in the document, the computer
system may capture a predetermined number of those typed words (as
described above) in a form of an entry provided to the computer
system. Thereafter, the computer system may provide the user with
phrases (i.e., sentence chunks), sentence, paragraphs, etc., from
previously created documents, based on the entry (i.e., the words)
entered by the user. Hence, the user may automatically obtain
relevant text from previously created documents, while the user is
creating a new document and/or modifying and exiting document.
[0109] In other embodiments, the computer system may reuse text
from other types of documents, such as medical notes. Particularly,
the computer system may parse previously created medical notes to
obtain the stored text. Furthermore, as described above, the
computer system also may identify, tag, remove, etc., named
entities. For instance, the computer system may tag and/or remove
named entities such as date, patient's name, weight, etc. As the
user (e.g., a physician) is creating a document, such a SOAP
(subjective, objective, assessment, and plan) note, the computer
system may retrieve relevant text from the stored text (notably, in
this embodiment, the stored text may consist of previously created,
parsed SOAP notes).
[0110] As described above, the user may provide an entry to the
computer system in numerous ways. Hence, for example, the user may
begin dictating the SOAP note, and as the user dictates (or
dictates a predetermined minimum number of words), the computer
system may provide relevant text (retrieved from previously created
SOAP notes, which had been parsed and may comprise the stored
text), based on the dictated words (i.e., based on the entry
provided by user). Alternatively, the user may type or begin typing
the SOAP note, and as the user types, the computer system may
display the relevant text to the user. As mentioned above, the
relevant text may be displayed simultaneously with the text being
entered by the user, whether via dictation, keyboard strokes, or
other entry methods.
[0111] Although the above description relates to legal and medical
documents, it should be appreciated that this invention is not so
limited. Accordingly, in other embodiments, the computer system may
parse any number of other types of documents. Hence, the stored
text, likewise, may comprise any number of sentence chunks,
sentences, sentence sequences (i.e., multiple sentences that do not
form a paragraph), paragraphs, and combinations thereof. Moreover,
the computer system may provide relevant text for any number of
types of documents being created by the user based on entries
received from the user.
[0112] In some embodiments, the computer system also may
automatically replace previously identified named entities. Hence,
certain named entities may be contained in one or more
predetermined locations (e.g., name, date, address), and may be
automatically substituted in place of the identified named entities
in the relevant text. For instance, in a document that requires a
name (e.g., name of a plaintiff), the computer system may
automatically substitute the identified named entities with the
name that correspond to such field. More specifically, the name may
be contained in another program, list, database, spreadsheet, or
other storage form and may be retried by the computer system
automatically, after the user has identified a set of new named
entities that should replace the identified named entities.
[0113] The illustrations of the embodiments described herein are
intended to provide a general understanding of the structure of the
various embodiments. The illustrations are not intended to serve as
a complete description of all of the elements and features of
apparatus and systems that utilize the structures or methods
described herein. Many other embodiments may be apparent to those
of ordinary skill in the art upon reviewing the disclosure. Other
embodiments may be utilized and derived from the disclosure, such
that structural and logical substitutions and changes may be made
without departing from the scope of the disclosure. Additionally,
the illustrations are merely representational and may not be drawn
to scale. Certain proportions within the illustrations may be
exaggerated, while other proportions may be minimized. Accordingly,
the disclosure and the figures are to be regarded as illustrative
rather than restrictive.
[0114] The above disclosed subject matter is to be considered
illustrative, and not restrictive, and the appended claims are
intended to cover all such modifications, enhancements, and other
embodiments which fall within the true spirit and scope of the
present disclosed subject matter. Thus, to the maximum extent
allowed by law, the scope of the present disclosed subject matter
is to be determined by the broadest permissible interpretation of
the following claims and their equivalents, and shall not be
restricted or limited
[0115] All patents, patent applications, and publications mentioned
herein are hereby incorporated by reference in their entireties.
However, where a patent, patent application, or publication
containing express definitions is incorporated by reference, those
express definitions should be understood to apply to the
incorporated patent, patent application, or publication in which
they are found, and not to the remainder of the text of this
application, in particular the claims of this application.
[0116] The present invention may be embodied in other specific
forms without departing from its spirit or essential
characteristics. The described embodiments are to be considered in
all respects only as illustrative and not restrictive. The scope of
the invention is, therefore, indicated by the appended claims
rather than by the foregoing description. All changes that come
within the meaning and range of equivalency of the claims are to be
embraced within their scope.
* * * * *
References