U.S. patent application number 16/394219 was filed with the patent office on 2019-08-15 for weighted annotation evaluation.
The applicant listed for this patent is INTERNATIONAL BUSINESS MACHINES CORPORATION. Invention is credited to Patrick W. Fink, Kristin E. McNeil, Philip E. Parker, David B. Werts.
Application Number | 20190251155 16/394219 |
Document ID | / |
Family ID | 59958862 |
Filed Date | 2019-08-15 |
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United States Patent
Application |
20190251155 |
Kind Code |
A1 |
Fink; Patrick W. ; et
al. |
August 15, 2019 |
WEIGHTED ANNOTATION EVALUATION
Abstract
A method for providing annotation summaries for annotations is
provided. The method may include receiving annotations associated
with analyzed unstructured data. The method may further include
sorting the received annotations. Additionally, the method may
include receiving focal points on the analyzed unstructured data.
The method may also include extracting the sorted annotations
associated with the focal points. The method may further include
normalizing terms and phrases associated with the extracted
annotations. The method may also include determining topics based
on the normalized terms and phrases associated with the extracted
annotations. The method may further include grouping the extracted
annotations based on the determined topics. The method may also
include summarizing the grouped annotations to generate a
summarized annotation. The method may further include replacing the
extracted annotations with the summarized annotation. The method
may also include presenting the summarized annotation in place of
the extracted annotations.
Inventors: |
Fink; Patrick W.;
(Charlotte, NC) ; McNeil; Kristin E.; (Charlotte,
NC) ; Parker; Philip E.; (York, SC) ; Werts;
David B.; (Charlotte, NC) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
INTERNATIONAL BUSINESS MACHINES CORPORATION |
ARMONK |
NY |
US |
|
|
Family ID: |
59958862 |
Appl. No.: |
16/394219 |
Filed: |
April 25, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
15085106 |
Mar 30, 2016 |
10318622 |
|
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16394219 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 3/04842 20130101;
G06F 3/0485 20130101; G06F 40/169 20200101 |
International
Class: |
G06F 17/24 20060101
G06F017/24; G06F 3/0484 20060101 G06F003/0484; G06F 3/0485 20060101
G06F003/0485 |
Claims
1. A computer program product for providing at least one annotation
summary for a plurality of annotations associated with at least one
analyzed unstructured data, comprising: one or more
computer-readable storage devices and program instructions stored
on at least one of the one or more computer-readable storage
devices, the program instructions executable by a processor, the
program instructions comprising: program instructions to extract
and receive the at least one analyzed unstructured data, wherein
the at least one analyzed unstructured data is associated with a
document based on an audio, video, or image file; program
instructions to receive the plurality of annotations associated
with the at least one analyzed unstructured data from at least one
common analysis structure (CAS); program instructions to sort the
received plurality of annotations by sorting the received plurality
of annotations based on at least one annotation type; program
instructions to receive at least one focal point on the at least
one analyzed unstructured data, wherein the at least one focal
point is based on text; program instructions to extract the sorted
plurality of annotations associated with the received at least one
focal point; program instructions to normalize a plurality of terms
and a plurality of phrases associated with the extracted plurality
of annotations based on at least one unified modeling language
structure; program instructions to determine at least one topic
based on the normalized plurality of terms and the normalized
plurality of phrases associated with the extracted plurality of
annotations by comparing the normalized terms and the normalized
phrases associated with the extracted annotations to at least one
ontology associated with the analyzed unstructured data, and
scoring the normalized terms and the normalized phrases associated
with the extracted annotations based on the comparison and at least
one relation threshold value; program instructions to group the
extracted plurality of annotations based on the determined at least
one topic; program instructions to summarize the grouped plurality
of annotations to generate at least one summarized annotation;
program instructions to replace the extracted plurality of
annotations with the at least one summarized annotation; program
instructions to present the at least one summarized annotation in
place of the extracted plurality of annotations on the at least one
analyzed unstructured data; and in response to receiving at least
one user action, program instructions to display the extracted
plurality of annotations associated with the at least one
summarized annotation.
Description
BACKGROUND
[0001] The present invention relates generally to the field of
computing, and more specifically, to data analysis.
[0002] Generally, text analytics/frameworks such as an unstructured
information management architecture (UIMA) may be used as a
framework for analyzing data. Specifically, the text analytics may
use analysis engines and annotators to analyze unstructured data
that may include documents, audio, video, and images. Furthermore,
the text analytics/frameworks may present the analysis results on
data structures, such as a common analysis structure (CAS), and may
typically include associating annotations with the unstructured
data, such as annotating the names of persons, organizations,
locations, facilities, and products, which are not explicitly
tagged or annotated in the unstructured data. For example, the text
analytics/frameworks may use analysis engines and annotators to
analyze the unstructured data associated with medical evaluation
reports on patients in order to determine indicators of medical
injury. Specifically, based on a patient medical report, the text
analytics/frameworks may extract and annotate terms that are
determined to be indicators of medical injury, such as the terms
"fall," "pain," "other injuries," "other injuries to her left
ankle," "swelling," "pain," "pain over the Achilles tendon,"
"pain," "ankle injury," "ankle sprain," "small fracture," "some
pain," and "fracture."
SUMMARY
[0003] A method for providing at least one annotation summary for a
plurality of annotations associated with at least one analyzed
unstructured data is provided. The method may include receiving the
plurality of annotations associated with the at least one analyzed
unstructured data. The method may further include sorting the
received plurality of annotations. Additionally, the method may
include receiving at least one focal point on the at least one
analyzed unstructured data. The method may also include extracting
the sorted plurality of annotations associated with the received at
least one focal point. The method may further include normalizing a
plurality of terms and a plurality of phrases associated with the
extracted plurality of annotations. The method may also include
determining at least one topic based on the normalized plurality of
terms and the normalized plurality of phrases associated with the
extracted plurality of annotations. The method may further include
grouping the extracted plurality of annotations based on the
determined at least one topic. The method may also include
summarizing the grouped plurality of annotations to generate at
least one summarized annotation. The method may further include
replacing the extracted plurality of annotations with the at least
one summarized annotation. The method may also include presenting
the at least one summarized annotation in place of the extracted
plurality of annotations on the at least one analyzed unstructured
data.
[0004] A computer system for providing at least one annotation
summary for a plurality of annotations associated with at least one
analyzed unstructured data is provided. The computer system may
include one or more processors, one or more computer-readable
memories, one or more computer-readable tangible storage devices,
and program instructions stored on at least one of the one or more
storage devices for execution by at least one of the one or more
processors via at least one of the one or more memories, whereby
the computer system is capable of performing a method. The method
may include receiving the plurality of annotations associated with
the at least one analyzed unstructured data. The method may further
include sorting the received plurality of annotations.
Additionally, the method may include receiving at least one focal
point on the at least one analyzed unstructured data. The method
may also include extracting the sorted plurality of annotations
associated with the received at least one focal point. The method
may further include normalizing a plurality of terms and a
plurality of phrases associated with the extracted plurality of
annotations. The method may also include determining at least one
topic based on the normalized plurality of terms and the normalized
plurality of phrases associated with the extracted plurality of
annotations. The method may further include grouping the extracted
plurality of annotations based on the determined at least one
topic. The method may also include summarizing the grouped
plurality of annotations to generate at least one summarized
annotation. The method may further include replacing the extracted
plurality of annotations with the at least one summarized
annotation. The method may also include presenting the at least one
summarized annotation in place of the extracted plurality of
annotations on the at least one analyzed unstructured data.
[0005] A computer program product for providing at least one
annotation summary for a plurality of annotations associated with
at least one analyzed unstructured data is provided. The computer
program product may include one or more computer-readable storage
devices and program instructions stored on at least one of the one
or more tangible storage devices, the program instructions
executable by a processor. The computer program product may include
program instructions to receive the plurality of annotations
associated with the at least one analyzed unstructured data. The
computer program product may further include program instructions
to sort the received plurality of annotations. Additionally, the
computer program product may also include program instructions to
receive at least one focal point on the at least one analyzed
unstructured data. The computer program product may further include
program instructions to extract the sorted plurality of annotations
associated with the received at least one focal point. The computer
program product may also include program instructions to normalize
a plurality of terms and a plurality of phrases associated with the
extracted plurality of annotations. The computer program product
may further include program instructions to determine at least one
topic based on the normalized plurality of terms and the normalized
plurality of phrases associated with the extracted plurality of
annotations. The computer program product may also include program
instructions to group the extracted plurality of annotations based
on the determined at least one topic. The computer program product
may further include program instructions to summarize the grouped
plurality of annotations to generate at least one summarized
annotation. The computer program product may also include program
instructions to replace the extracted plurality of annotations with
the at least one summarized annotation. The computer program
product may further include program instructions to present the at
least one summarized annotation in place of the extracted plurality
of annotations on the at least one analyzed unstructured data.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0006] These and other objects, features and advantages of the
present invention will become apparent from the following detailed
description of illustrative embodiments thereof, which is to be
read in connection with the accompanying drawings. The various
features of the drawings are not to scale as the illustrations are
for clarity in facilitating one skilled in the art in understanding
the invention in conjunction with the detailed description. In the
drawings:
[0007] FIG. 1 illustrates a networked computer environment
according to one embodiment;
[0008] FIG. 2 is an operational flowchart illustrating the steps
carried out by a program for providing annotation summaries to
annotations associated with analyzed unstructured data according to
one embodiment;
[0009] FIG. 3 is a block diagram of the system architecture of a
program for providing annotation summaries to annotations
associated with analyzed unstructured data according to one
embodiment;
[0010] FIG. 4 is a block diagram of an illustrative cloud computing
environment including the computer system depicted in FIG. 1, in
accordance with an embodiment of the present disclosure; and
[0011] FIG. 5 is a block diagram of functional layers of the
illustrative cloud computing environment of FIG. 4, in accordance
with an embodiment of the present disclosure.
DETAILED DESCRIPTION
[0012] Detailed embodiments of the claimed structures and methods
are disclosed herein; however, it can be understood that the
disclosed embodiments are merely illustrative of the claimed
structures and methods that may be embodied in various forms. This
invention may, however, be embodied in many different forms and
should not be construed as limited to the exemplary embodiments set
forth herein. In the description, details of well-known features
and techniques may be omitted to avoid unnecessarily obscuring the
presented embodiments.
[0013] Embodiments of the present invention relate generally to the
field of computing, and more particularly, to data analysis. The
following described exemplary embodiments provide a system, method
and program product for providing annotation summaries to
annotations based on analysis results associated with unstructured
data. Therefore, the present embodiment has the capacity to improve
the technical field associated with data analysis by filtering out
redundant and related annotations based on the analysis results
associated with the unstructured data. Specifically, the present
embodiment may receive annotations associated with analyzed
unstructured data, determine topics associated with the
annotations, and summarize the annotations based on the determined
topics.
[0014] As previously described with respect to data analysis, text
analytics/frameworks such as UIMA may use analysis engines and
annotators to analyze unstructured data that may include documents,
audio, video, and images. For example, and as previously described,
the text analytics/frameworks may analyze the unstructured data
associated with medical evaluation reports by extracting and
annotating medical injury indicators. However, because the analysis
engines and annotators may broadly analyze the unstructured data,
the text analytics/frameworks may extract and annotate redundant
terms and related terms resulting in excessive analysis results.
Specifically, and as previously described, the text
analytics/frameworks may use analysis engines to annotate medical
injury indicators such as "fall," "pain," "other injuries," "other
injuries to her left ankle," "swelling," "pain," "pain over the
Achilles tendon," "pain," "ankle injury," "ankle sprain," "small
fracture," "some pain," and "fracture." Therefore, the text
analytics/frameworks may extract and annotate redundant terms such
as "pain" and "pain," and related terms such as "other injuries,"
"other injuries to her left ankle," "swelling," "pain," "pain over
the Achilles tendon," and "ankle injury," as well as "fracture" and
"small fracture," thereby resulting in excessive extractions and
annotations. As such, it may be advantageous, among other things,
to provide a system, method and program product for providing
annotation summaries to annotations based on analysis results
associated with unstructured data. Specifically, the system,
method, and program product may receive annotations associated with
analyzed unstructured data, determine topics associated with the
annotations, and summarize the annotations based on the determined
topics.
[0015] According to at least one implementation of the present
embodiment, annotations associated with analyzed unstructured data
may be received. Next, the received annotations may be sorted.
Then, focal points associated with the analyzed unstructured data
may be received. Next, the sorted annotations associated with the
received focal points may be extracted. Then, terms and phrases
associated with the extracted annotations may be normalized. Next,
topics associated with the extracted annotations may be determined
based on the normalized terms and phrases. Then, based on the
determined topics, the extracted annotations may be grouped. Next,
the grouped annotations may be summarized. Then, the extracted
annotations associated with the received focal points may be
replaced with the summarized annotations. Next, the summarized
annotations may be presented on the analyzed unstructured data.
[0016] The present invention may be a system, a method, and/or a
computer program product. The computer program product may include
a computer readable storage medium (or media) having computer
readable program instructions thereon for causing a processor to
carry out aspects of the present invention.
[0017] The computer readable storage medium can be a tangible
device that can retain and store instructions for use by an
instruction execution device. The computer readable storage medium
may be, for example, but is not limited to, an electronic storage
device, a magnetic storage device, an optical storage device, an
electromagnetic storage device, a semiconductor storage device, or
any suitable combination of the foregoing. A non-exhaustive list of
more specific examples of the computer readable storage medium
includes the following: a portable computer diskette, a hard disk,
a random access memory (RAM), a read-only memory (ROM), an erasable
programmable read-only memory (EPROM or Flash memory), a static
random access memory (SRAM), a portable compact disc read-only
memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a
floppy disk, a mechanically encoded device such as punch-cards or
raised structures in a groove having instructions recorded thereon,
and any suitable combination of the foregoing. A computer readable
storage medium, as used herein, is not to be construed as being
transitory signals per se, such as radio waves or other freely
propagating electromagnetic waves, electromagnetic waves
propagating through a waveguide or other transmission media (e.g.,
light pulses passing through a fiber-optic cable), or electrical
signals transmitted through a wire.
[0018] Computer readable program instructions described herein can
be downloaded to respective computing/processing devices from a
computer readable storage medium or to an external computer or
external storage device via a network, for example, the Internet, a
local area network, a wide area network and/or a wireless network.
The network may comprise copper transmission cables, optical
transmission fibers, wireless transmission, routers, firewalls,
switches, gateway computers, and/or edge servers. A network adapter
card or network interface in each computing/processing device
receives computer readable program instructions from the network
and forwards the computer readable program instructions for storage
in a computer readable storage medium within the respective
computing/processing device.
[0019] Computer readable program instructions for carrying out
operations of the present invention may be assembler instructions,
instruction-set-architecture (ISA) instructions, machine
instructions, machine dependent instructions, microcode, firmware
instructions, state-setting data, or either source code or object
code written in any combination of one or more programming
languages, including an object oriented programming language such
as Java, Smalltalk, C++ or the like, and conventional procedural
programming languages, such as the "C" programming language or
similar programming languages. The computer readable program
instructions may execute entirely on the user's computer, partly on
the user's computer, as a stand-alone software package, partly on
the user's computer and partly on a remote computer or entirely on
the remote computer or server. In the latter scenario, the remote
computer may be connected to the user's computer through any type
of network, including a local area network (LAN) or a wide area
network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider). In some embodiments, electronic circuitry
including, for example, programmable logic circuitry,
field-programmable gate arrays (FPGA), or programmable logic arrays
(PLA) may execute the computer readable program instructions by
utilizing state information of the computer readable program
instructions to personalize the electronic circuitry, in order to
perform aspects of the present invention.
[0020] Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems), and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, can be implemented by computer readable
program instructions.
[0021] These computer readable program instructions may be provided
to a processor of a general purpose computer, special purpose
computer, or other programmable data processing apparatus to
produce a machine, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or blocks.
These computer readable program instructions may also be stored in
a computer readable storage medium that can direct a computer, a
programmable data processing apparatus, and/or other devices to
function in a particular manner, such that the computer readable
storage medium having instructions stored therein comprises an
article of manufacture including instructions which implement
aspects of the function/act specified in the flowchart and/or block
diagram block or blocks.
[0022] The computer readable program instructions may also be
loaded onto a computer, other programmable data processing
apparatus, or other device to cause a series of operational steps
to be performed on the computer, other programmable apparatus or
other device to produce a computer implemented process, such that
the instructions which execute on the computer, other programmable
apparatus, or other device implement the functions/acts specified
in the flowchart and/or block diagram block or blocks.
[0023] The flowchart and block diagrams in the Figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods, and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, segment, or portion of instructions, which comprises one
or more executable instructions for implementing the specified
logical function(s). In some alternative implementations, the
functions noted in the block may occur out of the order noted in
the figures. For example, two blocks shown in succession may, in
fact, be executed substantially concurrently, or the blocks may
sometimes be executed in the reverse order, depending upon the
functionality involved. It will also be noted that each block of
the block diagrams and/or flowchart illustration, and combinations
of blocks in the block diagrams and/or flowchart illustration, can
be implemented by special purpose hardware-based systems that
perform the specified functions or acts or carry out combinations
of special purpose hardware and computer instructions.
[0024] The following described exemplary embodiments provide a
system, method, and program product for providing annotation
summaries to annotations associated with analyzed unstructured
data.
[0025] According to at least one implementation, annotations
associated with analyzed unstructured data may be received. Next,
the received annotations may be sorted. Then, focal points
associated with the analyzed unstructured data may be received.
Next, the sorted annotations associated with the received focal
points may be extracted. Then, terms and phrases associated with
the extracted annotations may be normalized. Next, topics
associated with the extracted annotations may be determined based
on the normalized terms and phrases. Then, based on the determined
topics, the extracted annotations may be grouped. Next, the grouped
annotations may be summarized. Then, the extracted annotations
associated with the received focal points may be replaced with the
summarized annotations. Next, the summarized annotations may be
presented on the analyzed unstructured data.
[0026] Referring now to FIG. 1, an exemplary networked computer
environment 100 in accordance with one embodiment is depicted. The
networked computer environment 100 may include a computer 102 with
a processor 104 and a data storage device 106 that is enabled to
run an annotation summarization program 108A and a software program
114. The software program 114 may be an application program such as
IBM.RTM. Advanced Care Insights (IBM and all IBM--based trademarks
and logos are trademarks or registered trademarks of International
Business Machines and/or its affiliates). The annotation
summarization program 108A may communicate with the software
program 114. The networked computer environment 100 may also
include a server 112 that is enabled to run an annotation
summarization program 108B and a communication network 110. The
networked computer environment 100 may include a plurality of
computers 102 and servers 112, only one of which is shown for
illustrative brevity.
[0027] According to at least one implementation, the present
embodiment may also include a database 116, which may be running on
server 112. The communication network may include various types of
communication networks, such as a wide area network (WAN), local
area network (LAN), a telecommunication network, a wireless
network, a public switched network and/or a satellite network. It
may be appreciated that FIG. 1 provides only an illustration of one
implementation and does not imply any limitations with regard to
the environments in which different embodiments may be implemented.
Many modifications to the depicted environments may be made based
on design and implementation requirements.
[0028] The client computer 102 may communicate with server computer
112 via the communications network 110. The communications network
110 may include connections, such as wire, wireless communication
links, or fiber optic cables. As will be discussed with reference
to FIG. 3, server computer 112 may include internal components 800a
and external components 900a, respectively, and client computer 102
may include internal components 800b and external components 900b,
respectively. Server computer 112 may also operate in a cloud
computing service model, such as Software as a Service (SaaS),
Platform as a Service (PaaS), or Infrastructure as a Service
(IaaS). Server 112 may also be located in a cloud computing
deployment model, such as a private cloud, community cloud, public
cloud, or hybrid cloud. Client computer 102 may be, for example, a
mobile device, a telephone, a personal digital assistant, a
netbook, a laptop computer, a tablet computer, a desktop computer,
or any type of computing device capable of running a program and
accessing a network. According to various implementations of the
present embodiment, the annotation summarization program 108A, 108B
may interact with a database 116 that may be embedded in various
storage devices, such as, but not limited to a mobile device 102, a
networked server 112, or a cloud storage service.
[0029] According to the present embodiment, a program, such as an
annotation summarization program 108A and 108B may run on the
client computer 102 or on the server computer 112 via a
communications network 110. The annotation summarization program
108A, 108B may provide annotation summaries to annotations based on
analysis results associated with unstructured data. Specifically, a
user using a computer, such as computer 102, may run an annotation
summarization program 108A, 108B, that interacts with a software
program 114, to receive annotations associated with analyzed
unstructured data, determine the topics associated with the
received annotations, and summarize the received annotations based
on the determined topics.
[0030] Referring now to FIG. 2, an operational flowchart 200
illustrating the steps carried out by a program for providing
annotation summaries to annotations associated with analyzed
unstructured data is depicted. At 202, the annotation summarization
program 108A, 108B (FIG. 1) may receive annotations associated with
the analyzed unstructured data. For example, and as previously
described, a software program 114 (FIG. 1), such as IBM.RTM.
Advanced Care Insights, may analyze unstructured data that may
include a document such as a medical evaluation report.
Furthermore, based on the analysis, annotations may be generated on
the unstructured data, and the annotations and the analyzed
unstructured data may be stored on a data structure such as a
common analysis structure (CAS). For example, IBM.RTM. Advanced
Care Insights may analyze the medical evaluation report by
providing annotations on the medical evaluation report of the terms
and phrases that are determined to be medical injury indicators,
such as the terms and phrases "dry cracked nail," "chest pain,"
"shortness of breath," "smelling of toe," and "swelling of toe."
Specifically, the annotation may include a statement such as,
"smelling of toe is a medical injury indicator." As such, the
annotation summarization program 108A, 108B (FIG. 1) may interact
with the software program 114 (FIG. 1) and the CAS to receive the
annotations associated with the analyzed unstructured data.
[0031] Next, at 204, the annotation summarization program 108A,
108B (FIG. 1) may sort the received annotations. Specifically, the
annotation summarization program 108A, 108B (FIG. 1) may sort the
received annotations based on annotation type. For example, the
annotation summarization program 108A, 108B (FIG. 1) may receive
annotations based on a medical evaluation report that may include
annotated terms and phrases associated with annotation types such
as medical injury indicators, medical procedures, and medicines.
Specifically, the annotation summarization program 108A, 108B (FIG.
1) may receive annotations based on an annotation type, such as
medical injury, and may include the annotated terms and phrases
such as "dry cracked nail," "chest pain," "shortness of breath,"
"smelling of toe," and "swelling of toe." Furthermore, the
annotation summarization program 108A, 108B (FIG. 1) may receive
annotations based on an annotation type, such as medicines, and may
include the annotated terms and phrases such as "antifungal pills,"
"topical cream," "anticoagulants," "beta blockers," and
"diuretics." As such, the annotation summarization program 108A,
108B (FIG. 1) may sort the annotations by grouping the annotated
terms and phrases associated with medical injuries, and grouping
the annotated terms and phrases associated with medicines.
[0032] Then, at 206, the annotation summarization program 108A,
108B (FIG. 1) may receive focal points based on the analyzed
unstructured data. As previously described at step 202, the
annotation summarization program 108A, 108B (FIG. 1) may receive
annotations associated with analyzed unstructured data that may
include a document such as a medical evaluation report.
Furthermore, based on user input, the annotation summarization
program 108A, 108B (FIG. 1) may focus on different parts of the
analyzed unstructured data, thereby enabling users to choose the
annotations to summarize, by receiving focal points on the analyzed
unstructured data. Specifically, based on user input, the
annotation summarization program 108A, 108B (FIG. 1) may receive
focal points such as term focal points, phrase focal points,
sentence focal points, paragraph focal points, section focal
points, and document focal points. For example, based on user
input, the annotation summarization program 108A, 108B (FIG. 1) may
receive a paragraph focal point. Therefore, the annotation
summarization program 108A, 108B (FIG. 1) may focus on the
paragraph that is associated with the received paragraph focal
point.
[0033] Next, at 208, the annotation summarization program 108A,
108B (FIG. 1) may extract the sorted annotations associated with
the received focal points. As previously described at step 206,
based on received focal points, the annotation summarization
program 108A, 108B (FIG. 1) may focus on parts of the analyzed
unstructured data. Thereafter, the annotation summarization program
108A, 108B (FIG. 1) may extract the sorted annotations associated
with the received focal points. For example, the analyzed
unstructured data may include a document such as a medical
evaluation report. Furthermore, based on user input, the annotation
summarization program 108A, 108B (FIG. 1) may receive a paragraph
focal point to focus on a paragraph associated with the medical
evaluation report, whereby the paragraph may include sorted
annotations based on the annotation type "medical injury" that are
associated with the terms "dry cracked nail," "chest pain,"
"shortness of breath," "smelling of toe," and "swelling of toe."
Therefore, the annotation summarization program 108A, 108B (FIG. 1)
may extract the sorted annotations associated with the terms "dry
cracked nail," "chest pain," "shortness of breath," "smelling of
toe," and "swelling of toe."
[0034] Next, at 210, the annotation summarization program 108A,
108B (FIG. 1) may normalize the terms and phrases associated with
the extracted annotations. Specifically, the annotation
summarization program 108A, 108B (FIG. 1) may normalize the terms
and phrases associated with the extracted annotations based on a
unified modeling language structure. For example, and as previously
described at step 208, the annotation summarization program 108A,
108B (FIG. 1) may extract sorted annotations associated with terms
and phrases such as "dry cracked nail," "chest pain," "shortness of
breath," "smelling of toe," and "swelling of toe." Furthermore, the
annotation summarization program 108A, 108B (FIG. 1) may determine
that a unified modeling language structure based on medical terms
and phrases may associate the phrase "smelling of toe" with the
phrase "toe odor." Therefore, based on the unified modeling
language structure, the annotation summarization program 108A, 108B
(FIG. 1) may normalize the term "smelling of toe" to "toe
odor."
[0035] Then, at 212, the annotation summarization program 108A,
108B (FIG. 1) may determine topics associated with the extracted
annotations based on the normalized terms and phrases.
Specifically, the annotation summarization program 108A, 108B (FIG.
1) may determine topics associated with the extracted annotations
by comparing the normalized terms and phrases to ontologies, and
scoring the normalized terms and phrases based on the comparison.
More specifically, and as previously described at steps 208 and
210, the annotation summarization program 108A, 108B (FIG. 1) may
extract sorted annotations associated with a medical evaluation
report, and normalize the terms and phrases associated with the
extracted annotations. Thereafter, the annotation summarization
program 108A, 108B (FIG. 1) may determine topics associated with
the extracted annotations by comparing the normalized terms and
phrases to diseases, ailments, and symptoms based on medical
ontologies. Then, based on a relation threshold value, the
annotation summarization program 108A, 108B (FIG. 1) may score the
normalized terms based on the comparison. Specifically, the
annotation summarization program 108A, 108B (FIG. 1) may use the
relation threshold value to determine the normalized terms and
phrases degree of relation to the diseases, ailments, and symptoms
associated with the medical ontologies.
[0036] For example, the annotation summarization program 108A, 108B
(FIG. 1) may compare the normalized terms and phrases such as "dry
cracked nail," "toe odor," and "toe swelling" to diseases,
ailments, and symptoms associated with the medical ontologies.
Furthermore, the annotation summarization program 108A, 108B (FIG.
1) may set a relation threshold value of 50%, whereby normalized
terms that are related to a disease, ailment, and/or symptom
greater than (>) 50% are associated with that disease, ailment,
and/or symptom. Next, based on the comparison, the annotation
summarization program 108A, 108B (FIG. 1) may determine that the
normalized term "dry cracked nail" is 95% related to the topic "toe
fungus," the normalized term "toe odor" is 70% related to the topic
"toe fungus," and the normalized term "toe swelling" is 90% related
to the topic "toe fungus." Also, for example, the annotation
summarization program 108A, 108B (FIG. 1) may compare the
normalized terms and phrases such as "chest pain" and "shortness of
breath" to diseases, ailments, and symptoms associated with the
medical ontologies Then, based on the comparison, the annotation
summarization program 108A, 108B (FIG. 1) may determine that the
normalized term "chest pain" is 100% related to the topic "heart
attack," and that the normalized term "shortness of breath" is 95%
related to the topic "heart attack." Therefore, the annotation
summarization program 108A, 108B (FIG. 1) may determine that the
topic "toe fungus" may be associated with the extracted annotations
that include the normalized terms "dry cracked nail," "toe odor,"
and "toe swelling," and determine that the topic "heart attack" may
be associated with the extracted annotations that include the
normalized terms "chest pain" and "shortness of breath."
[0037] Next, at 214, the annotation summarization program 108A,
108B (FIG. 1) may group the extracted annotations based on the
determined topics. As previously described at step 212, the
annotation summarization program 108A, 108B (FIG. 1) may determine
topics associated with the extracted annotations based on the
normalized terms and phrases. For example, the annotation
summarization program 108A, 108B (FIG. 1) may determine that the
topic "toe fungus" may be associated with the extracted annotations
that include the normalized terms "dry cracked nail," "toe odor,"
and "toe swelling," and determine that the topic "heart attack" may
be associated with the extracted annotations that include the
normalized terms "chest pain" and "shortness of breath." Therefore,
the annotation summarization program 108A, 108B (FIG. 1) may group
the extracted annotation that includes the normalized phrase "dry
cracked nail" with the extracted annotation that includes the
normalized phrase "toe odor" as well as with the extracted
annotation that includes the normalized phrase "toe swelling."
Additionally, the annotation summarization program 108A, 108B (FIG.
1) may group the extracted annotation that includes the normalized
phrase "chest pain" with the extracted annotation that includes the
normalized phrase "shortness of breath."
[0038] Then, at 216, the annotation summarization program 108A,
108B (FIG. 1) may summarize the grouped annotations based on the
determined topics to generate a summarized annotation. As
previously described at steps 212 and 214, the annotation
summarization program 108A, 108B (FIG. 1) may determine topics to
associate with the extracted annotations, and then group the
extracted annotations based on the determined topics. As such, the
annotation summarization program 108A, 108B (FIG. 1) may summarize
the grouped annotations into at least one phrase and/or topic based
on the determined topic. For example, based on the determined topic
"toe fungus," the annotation summarization program 108A, 108B (FIG.
1) may group the extracted annotation that includes the normalized
phrase "dry cracked nail" with the extracted annotation that
includes the normalized phrase "toe odor" as well as with the
extracted annotation that includes the normalized phrase "toe
swelling" that are based on the annotation type "medical injury."
Thereafter, the annotation summarization program 108A, 108B (FIG.
1) may summarize the grouped annotations into at least one
phrase/topic such as "medical injury--toe fungus," and generate a
summarized annotation that includes "medical injury--toe
fungus."
[0039] Next, at 218, the annotation summarization program 108A,
108B (FIG. 1) may replace the extracted annotations with the
summarized annotation. As previously described at steps 206 and
208, based on user input, the annotation summarization program
108A, 108B (FIG. 1) may receive a paragraph focal point associated
with the analyzed unstructured data and extract the sorted
annotations associated with the received paragraph focal point.
Furthermore, and as previously described at steps 214 and 216, the
annotation summarization program 108A, 108B (FIG. 1) may group the
extracted annotations, and summarize the grouped annotations to
generate a summarized annotation. Therefore, the annotation
summarization program 108A, 108B (FIG. 1) may replace the extracted
annotations associated with the received paragraph focal point with
the summarized annotation. For example, the annotation
summarization program 108A, 108B (FIG. 1) may extract sorted
annotations associated with the phrases "dry cracked nail," "chest
pain," "shortness of breath," "smelling of toe," and "swelling of
toe" based on a received paragraph focal point. Thereafter, the
annotation summarization program 108A, 108B (FIG. 1) may group the
extracted annotations associated with the phrases "dry cracked
nail," "smelling of toe," and "swelling of toe" based on a
determined topic, such as "toe fungus," that is associated with the
normalized version of the terms and phrases included in the
extracted annotations. Then, the annotation summarization program
108A, 108B (FIG. 1) may summarize the grouped annotations to
generate a summarized annotation, such as "medical injury--toe
fungus." As such, the annotation summarization program 108A, 108B
(FIG. 1) may replace the extracted annotations associated with the
phrases "dry cracked nail," "smelling of toe," and "swelling of
toe" with the at least one summarized phrase "medical injury--toe
fungus."
[0040] Then, at 220, the annotation summarization program 108A,
108B (FIG. 1) may present the summarized annotation on the analyzed
unstructured data. As previously described at step 218, the
annotation summarization program 108A, 108B (FIG. 1) may replace
the extracted annotations with the summarized annotation.
Therefore, in place of the extracted annotations, the summarized
annotation may be presented on the analyzed unstructured data. For
example, the annotation summarization program 108A, 108B (FIG. 1)
may replace the extracted annotations associated with the phrases
"dry cracked nail," "smelling of toe," and "swelling of toe" with
the at least one summarized phrase "medical injury--toe fungus."
Therefore, on the paragraph associated with the received paragraph
focal point, the annotation summarization program 108A, 108B (FIG.
1) may present the summarized annotation "medical injury--toe
fungus" on the analyzed unstructured data in place of the extracted
annotations associated with the phrases "dry cracked nail,"
"smelling of toe," and "swelling of toe."
[0041] It may be appreciated that FIG. 2 provides only
illustrations of one implementation and does not imply any
limitations with regard to how different embodiments may be
implemented. Many modifications to the depicted environments may be
made based on design and implementation requirements. For example,
in response to a user action such as a user scrolling over or
clicking on the presented summarized annotation, the annotation
summarization program 108A, 108B (FIG. 1) may display the extracted
annotations that are associated with the summarized annotation. For
example, in response to a user scrolling over or clicking on the
summarized annotation "medical injury--toe fungus" on the analyzed
unstructured data, the annotation summarization program 108A, 108B
(FIG. 1) may display the extracted annotations associated with the
phrases "dry cracked nail," "smelling of toe," and "swelling of
toe."
[0042] FIG. 3 is a block diagram 300 of internal and external
components of computers depicted in FIG. 1 in accordance with an
illustrative embodiment of the present invention. It should be
appreciated that FIG. 3 provides only an illustration of one
implementation and does not imply any limitations with regard to
the environments in which different embodiments may be implemented.
Many modifications to the depicted environments may be made based
on design and implementation requirements.
[0043] Data processing system 800, 900 is representative of any
electronic device capable of executing machine-readable program
instructions. Data processing system 800, 900 may be representative
of a smart phone, a computer system, PDA, or other electronic
devices. Examples of computing systems, environments, and/or
configurations that may represented by data processing system 800,
900 include, but are not limited to, personal computer systems,
server computer systems, thin clients, thick clients, hand-held or
laptop devices, multiprocessor systems, microprocessor-based
systems, network PCs, minicomputer systems, and distributed cloud
computing environments that include any of the above systems or
devices.
[0044] User client computer 102 (FIG. 1), and network server 112
(FIG. 1) include respective sets of internal components 800 a, b
and external components 900 a, b illustrated in FIG. 3. Each of the
sets of internal components 800 a, b includes one or more
processors 820, one or more computer-readable RAMs 822, and one or
more computer-readable ROMs 824 on one or more buses 826, and one
or more operating systems 828 and one or more computer-readable
tangible storage devices 830. The one or more operating systems
828, the software program 114 (FIG. 1) and the annotation
summarization program 108A (FIG. 1) in client computer 102 (FIG.
1), and the annotation summarization program 108B (FIG. 1) in
network server computer 112 (FIG. 1) are stored on one or more of
the respective computer-readable tangible storage devices 830 for
execution by one or more of the respective processors 820 via one
or more of the respective RAMs 822 (which typically include cache
memory). In the embodiment illustrated in FIG. 3, each of the
computer-readable tangible storage devices 830 is a magnetic disk
storage device of an internal hard drive. Alternatively, each of
the computer-readable tangible storage devices 830 is a
semiconductor storage device such as ROM 824, EPROM, flash memory
or any other computer-readable tangible storage device that can
store a computer program and digital information.
[0045] Each set of internal components 800 a, b, also includes a
R/W drive or interface 832 to read from and write to one or more
portable computer-readable tangible storage devices 936 such as a
CD-ROM, DVD, memory stick, magnetic tape, magnetic disk, optical
disk or semiconductor storage device. A software program, such as
an annotation summarization program 108A and 108B (FIG. 1), can be
stored on one or more of the respective portable computer-readable
tangible storage devices 936, read via the respective R/W drive or
interface 832 and loaded into the respective hard drive 830.
[0046] Each set of internal components 800 a, b also includes
network adapters or interfaces 836 such as a TCP/IP adapter cards,
wireless Wi-Fi interface cards, or 3G or 4G wireless interface
cards or other wired or wireless communication links. The
annotation summarization program 108A (FIG. 1) and software program
114 (FIG. 1) in client computer 102 (FIG. 1), and the annotation
summarization program 108B (FIG. 1) in network server 112 (FIG. 1)
can be downloaded to client computer 102 (FIG. 1) from an external
computer via a network (for example, the Internet, a local area
network or other, wide area network) and respective network
adapters or interfaces 836. From the network adapters or interfaces
836, the annotation summarization program 108A (FIG. 1) and
software program 114 (FIG. 1) in client computer 102 (FIG. 1) and
the annotation summarization program 108B (FIG. 1) in network
server computer 112 (FIG. 1) are loaded into the respective hard
drive 830. The network may comprise copper wires, optical fibers,
wireless transmission, routers, firewalls, switches, gateway
computers, and/or edge servers.
[0047] Each of the sets of external components 900 a, b can include
a computer display monitor 920, a keyboard 930, and a computer
mouse 934. External components 900 a, b can also include touch
screens, virtual keyboards, touch pads, pointing devices, and other
human interface devices. Each of the sets of internal components
800 a, b also includes device drivers 840 to interface to computer
display monitor 920, keyboard 930, and computer mouse 934. The
device drivers 840, R/W drive or interface 832 and network adapter
or interface 836 comprise hardware and software (stored in storage
device 830 and/or ROM 824).
[0048] It is understood in advance that although this disclosure
includes a detailed description on cloud computing, implementation
of the teachings recited herein are not limited to a cloud
computing environment. Rather, embodiments of the present invention
are capable of being implemented in conjunction with any other type
of computing environment now known or later developed.
[0049] Cloud computing is a model of service delivery for enabling
convenient, on-demand network access to a shared pool of
configurable computing resources (e.g. networks, network bandwidth,
servers, processing, memory, storage, applications, virtual
machines, and services) that can be rapidly provisioned and
released with minimal management effort or interaction with a
provider of the service. This cloud model may include at least five
characteristics, at least three service models, and at least four
deployment models.
[0050] Characteristics are as follows:
[0051] On-demand self-service: a cloud consumer can unilaterally
provision computing capabilities, such as server time and network
storage, as needed automatically without requiring human
interaction with the service's provider.
[0052] Broad network access: capabilities are available over a
network and accessed through standard mechanisms that promote use
by heterogeneous thin or thick client platforms (e.g., mobile
phones, laptops, and PDAs).
[0053] Resource pooling: the provider's computing resources are
pooled to serve multiple consumers using a multi-tenant model, with
different physical and virtual resources dynamically assigned and
reassigned according to demand. There is a sense of location
independence in that the consumer generally has no control or
knowledge over the exact location of the provided resources but may
be able to specify location at a higher level of abstraction (e.g.,
country, state, or datacenter).
[0054] Rapid elasticity: capabilities can be rapidly and
elastically provisioned, in some cases automatically, to quickly
scale out and rapidly released to quickly scale in. To the
consumer, the capabilities available for provisioning often appear
to be unlimited and can be purchased in any quantity at any
time.
[0055] Measured service: cloud systems automatically control and
optimize resource use by leveraging a metering capability at some
level of abstraction appropriate to the type of service (e.g.,
storage, processing, bandwidth, and active user accounts). Resource
usage can be monitored, controlled, and reported providing
transparency for both the provider and consumer of the utilized
service.
[0056] Service Models are as follows:
[0057] Software as a Service (SaaS): the capability provided to the
consumer is to use the provider's applications running on a cloud
infrastructure. The applications are accessible from various client
devices through a thin client interface such as a web browser
(e.g., web-based e-mail). The consumer does not manage or control
the underlying cloud infrastructure including network, servers,
operating systems, storage, or even individual application
capabilities, with the possible exception of limited user-specific
application configuration settings.
[0058] Platform as a Service (PaaS): the capability provided to the
consumer is to deploy onto the cloud infrastructure
consumer-created or acquired applications created using programming
languages and tools supported by the provider. The consumer does
not manage or control the underlying cloud infrastructure including
networks, servers, operating systems, or storage, but has control
over the deployed applications and possibly application hosting
environment configurations.
[0059] Infrastructure as a Service (IaaS): the capability provided
to the consumer is to provision processing, storage, networks, and
other fundamental computing resources where the consumer is able to
deploy and run arbitrary software, which can include operating
systems and applications. The consumer does not manage or control
the underlying cloud infrastructure but has control over operating
systems, storage, deployed applications, and possibly limited
control of select networking components (e.g., host firewalls).
[0060] Deployment Models are as follows:
[0061] Private cloud: the cloud infrastructure is operated solely
for an organization. It may be managed by the organization or a
third party and may exist on-premises or off-premises.
[0062] Community cloud: the cloud infrastructure is shared by
several organizations and supports a specific community that has
shared concerns (e.g., mission, security requirements, policy, and
compliance considerations). It may be managed by the organizations
or a third party and may exist on-premises or off-premises.
[0063] Public cloud: the cloud infrastructure is made available to
the general public or a large industry group and is owned by an
organization selling cloud services.
[0064] Hybrid cloud: the cloud infrastructure is a composition of
two or more clouds (private, community, or public) that remain
unique entities but are bound together by standardized or
proprietary technology that enables data and application
portability (e.g., cloud bursting for load-balancing between
clouds).
[0065] A cloud computing environment is service oriented with a
focus on statelessness, low coupling, modularity, and semantic
interoperability. At the heart of cloud computing is an
infrastructure comprising a network of interconnected nodes.
[0066] Referring now to FIG. 4, illustrative cloud computing
environment 400 is depicted. As shown, cloud computing environment
400 comprises one or more cloud computing nodes 100 with which
local computing devices used by cloud consumers, such as, for
example, personal digital assistant (PDA) or cellular telephone
400A, desktop computer 400B, laptop computer 400C, and/or
automobile computer system 400N may communicate. Nodes 100 may
communicate with one another. They may be grouped (not shown)
physically or virtually, in one or more networks, such as Private,
Community, Public, or Hybrid clouds as described hereinabove, or a
combination thereof. This allows cloud computing environment 400 to
offer infrastructure, platforms and/or software as services for
which a cloud consumer does not need to maintain resources on a
local computing device. It is understood that the types of
computing devices 400A-N shown in FIG. 4 are intended to be
illustrative only and that computing nodes 100 and cloud computing
environment 400 can communicate with any type of computerized
device over any type of network and/or network addressable
connection (e.g., using a web browser).
[0067] Referring now to FIG. 5, a set of functional abstraction
layers 500 provided by cloud computing environment 400 (FIG. 4) is
shown. It should be understood in advance that the components,
layers, and functions shown in FIG. 5 are intended to be
illustrative only and embodiments of the invention are not limited
thereto. As depicted, the following layers and corresponding
functions are provided:
[0068] Hardware and software layer 60 includes hardware and
software components. Examples of hardware components include:
mainframes 61; RISC (Reduced Instruction Set Computer) architecture
based servers 62; servers 63; blade servers 64; storage devices 65;
and networks and networking components 66. In some embodiments,
software components include network application server software 67
and database software 68.
[0069] Virtualization layer 70 provides an abstraction layer from
which the following examples of virtual entities may be provided:
virtual servers 71; virtual storage 72; virtual networks 73,
including virtual private networks; virtual applications and
operating systems 74; and virtual clients 75.
[0070] In one example, management layer 80 may provide the
functions described below. Resource provisioning 81 provides
dynamic procurement of computing resources and other resources that
are utilized to perform tasks within the cloud computing
environment. Metering and Pricing 82 provide cost tracking as
resources are utilized within the cloud computing environment, and
billing or invoicing for consumption of these resources. In one
example, these resources may comprise application software
licenses. Security provides identity verification for cloud
consumers and tasks, as well as protection for data and other
resources. User portal 83 provides access to the cloud computing
environment for consumers and system administrators. Service level
management 84 provides cloud computing resource allocation and
management such that required service levels are met. Service Level
Agreement (SLA) planning and fulfillment 85 provide pre-arrangement
for, and procurement of, cloud computing resources for which a
future requirement is anticipated in accordance with an SLA.
[0071] Workloads layer 90 provides examples of functionality for
which the cloud computing environment may be utilized. Examples of
workloads and functions which may be provided from this layer
include: mapping and navigation 91; software development and
lifecycle management 92; virtual classroom education delivery 93;
data analytics processing 94; transaction processing 95; and
annotation summarization 96. An annotation summarization program
108A, 108B (FIG. 1) may be offered "as a service in the cloud"
(i.e., Software as a Service (SaaS)) for applications running on
mobile devices 102 (FIG. 1) and may provide annotation summaries to
annotations associated with analyzed unstructured data.
[0072] The descriptions of the various embodiments of the present
invention have been presented for purposes of illustration, but are
not intended to be exhaustive or limited to the embodiments
disclosed. Many modifications and variations will be apparent to
those of ordinary skill in the art without departing from the scope
of the described embodiments. The terminology used herein was
chosen to best explain the principles of the embodiments, the
practical application or technical improvement over technologies
found in the marketplace, or to enable others of ordinary skill in
the art to understand the embodiments disclosed herein.
* * * * *