U.S. patent application number 14/943427 was filed with the patent office on 2017-05-18 for computer-implemented cognitive system for assessing subjective question-answers.
The applicant listed for this patent is International Business Machines Corporation. Invention is credited to Sathish R. Indurthi, Mitesh M. Khapra, Yedendra B. Shrinivasan, Mitesh H. Vasa.
Application Number | 20170140277 14/943427 |
Document ID | / |
Family ID | 58643564 |
Filed Date | 2017-05-18 |
United States Patent
Application |
20170140277 |
Kind Code |
A1 |
Indurthi; Sathish R. ; et
al. |
May 18, 2017 |
COMPUTER-IMPLEMENTED COGNITIVE SYSTEM FOR ASSESSING SUBJECTIVE
QUESTION-ANSWERS
Abstract
A cognitive system that automatically assesses subjective
answers may be provided. A cognitive engine executing on one or
more processors may determine whether a statement parsed from a
subjective answer by natural language processing technique is
accurate or inaccurate, for each of the plurality of statements
based on matching the statement with information associated with a
domain of a question from a plurality of data sources, according to
an accuracy threshold. An overall assessment of the answer may be
automatically determined based on a number of statements determined
to be accurate, a number of statements determined to be inaccurate,
a number of duplicate statements in the answer relative to a total
number of statements in the answer. A visual graphics representing
accurate and inaccurate statements may be presented or displayed,
allowing a user to interact with the visual graphics to modify the
assessment.
Inventors: |
Indurthi; Sathish R.;
(Bangalore, IN) ; Khapra; Mitesh M.; (Bangalore,
IN) ; Shrinivasan; Yedendra B.; (Yorktown Heights,
NY) ; Vasa; Mitesh H.; (Bangalore, IN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
International Business Machines Corporation |
Armonk |
NY |
US |
|
|
Family ID: |
58643564 |
Appl. No.: |
14/943427 |
Filed: |
November 17, 2015 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06N 5/04 20130101; G06F
16/24522 20190101; G09B 7/02 20130101 |
International
Class: |
G06N 5/04 20060101
G06N005/04; G06F 17/30 20060101 G06F017/30 |
Claims
1. A computer-implemented cognitive system, comprising: one or more
hardware processors; a cognitive engine operable to execute on one
or more of the hardware processors and further operable to receive
first data representative of a domain associated with a question,
the cognitive engine further operable to search a database of
sources and retrieve information associated with the domain, the
cognitive engine further operable to receive second data
representative of an answer in an essay form to the question, the
second data comprising a plurality of statements that make up the
answer in the essay form, the cognitive engine further operable to
determine whether a statement is accurate or inaccurate, for each
of the plurality of statements based on matching the statement with
the information associated with the domain according to an accuracy
threshold; a scoring module operable to execute on one or more of
the hardware processors and further operable to determine an
overall score for the answer based on a number of statements in the
answer in the essay form determined to be accurate, a number of
statements in the answer in the essay form determined to be
inaccurate, a number of duplicate statements in the answer in the
essay form relative to a total number of statements in the answer
in the essay form; and a visual assessment module operable to
generate a visual graphics representing accurate and inaccurate
statements determined by the cognitive engine and the overall
score; a graphical user interface operable to display the visual
graphics and interact with a user to allow the user to modify the
overall score; and a comparative assessment module operable to
execute on one or more of the hardware processors and further
operable to search a database of answers to the question to
identify a plurality of comparative statements comprising answers
provided by a plurality of individuals in answering the question,
the comparative assessment module further operable to provide the
plurality of comparative statements to the cognitive engine,
wherein the cognitive engine matches the statement with the
plurality of comparative statements to determine whether the
statement is accurate or inaccurate, the comparative statements
comprising an essay-type of answers given by the plurality of
individuals.
2. (canceled)
3. The system of claim 1, wherein the cognitive engine invokes the
comparative assessment module for determining whether the statement
is accurate or inaccurate, responsive to determining that the
statement does not match the information associated with the
domain.
4. The system of claim 1, wherein a computer-implemented natural
language technique classifies the question and determines the
domain.
5. The system of claim 1, wherein a computer-implemented natural
language technique parses the answer, extracts the plurality of
statements and identifies duplicate statements in the answer, and
annotates each of the plurality of statements as fact or
opinion.
6. A computer-implemented method of assessing a subjective answer,
the method performed by one or more hardware processors,
comprising: receiving first data representative of a domain
associated with a question; receiving second data representative of
an answer in an essay form to the question, the second data
comprising a plurality of statements that make up the answer in the
essay form; searching a database of sources to retrieve information
associated with the domain; determining whether a statement is
accurate or inaccurate, for each of the plurality of statements
based on matching the statement with the information associated
with the domain according to an accuracy threshold; determining an
overall score for the answer based on a number of statements in the
answer in the essay form determined to be accurate, a number of
statements in the answer in the essay form determined to be
inaccurate, a number of duplicate statements in the answer in the
essay form relative to a total number of statements in the answer;
generating visual graphics representing accurate and inaccurate
statements and the overall score; displaying the visual graphics on
a display device; searching a database of answers to the question
to identify a plurality of comparative statements comprising
answers provided by a plurality of individuals in answering the
question; matching the statement with the plurality of comparative
statements to determine whether the statement is accurate or
inaccurate, the comparative statements identified from an
essay-type of answers given by the plurality of individuals
responsive to the question.
7. The method of claim 6, further comprising: interacting with a
user by a computer-implemented user interface to allow the user to
modify the overall score.
8. The method of claim 7, further comprising: learning by one or
more of the hardware processors, to determine whether one or more
of the plurality of statements is accurate or inaccurate further
based on the overall score responsive to the user modifying the
overall score.
9. (canceled)
10. The method of claim 6, wherein the searching of the database of
answers to the question and the matching the statement with the
plurality of comparative statements, are performed responsive to
determining that the statement does not match the information
associated with the domain.
11. The method of claim 6, further comprising performing a
computer-implemented natural language technique that classifies the
question and determines the domain.
12. The method of claim 6, further comprising performing a
computer-implemented natural language technique that parses the
answer, extracts the plurality of statements and identifies
duplicate statements in the answer, and annotates each of the
plurality of statements as fact or opinion.
13. A non-transitory computer readable storage medium storing a
program of instructions executable by a machine to perform a method
of assessing a subjective answer, the method comprising: receiving
first data representative of a domain associated with a question;
receiving second data representative of an answer in an essay form
to the question, the second data comprising a plurality of
statements that make up the answer in the essay form; searching a
database of sources to retrieve information associated with the
domain; determining whether a statement is accurate or inaccurate,
for each of the plurality of statements based on matching the
statement with the information associated with the domain according
to an accuracy threshold; determining an overall score for the
answer based on a number of statements in the answer in the essay
form determined to be accurate, a number of statements in the
answer in the essay form determined to be inaccurate, a number of
duplicate statements in the answer in the essay form relative to a
total number of statements in the answer; generating visual
graphics representing accurate and inaccurate statements and the
overall score; displaying the visual graphics on a display device;
searching a database of answers to the question to identify a
plurality of comparative statements comprising answers provided by
a plurality of individuals in answering the question; matching the
statement with the plurality of comparative statements to determine
whether the statement is accurate or inaccurate, the comparative
statements identified from an essay-type of answers given by the
plurality of individuals responsive to the question.
14. The non-transitory computer readable storage medium of claim
13, further comprising: interacting with a user by a
computer-implemented user interface to allow the user to modify the
overall score.
15. The non-transitory computer readable storage medium of claim
14, further comprising: learning by one or more of the hardware
processors, to determine whether one or more of the plurality of
statements is accurate or inaccurate further based on the overall
score that responsive to the user modifying the overall score.
16. (canceled)
17. The non-transitory computer readable storage medium of claim
13, wherein the searching of the database of answers to the
question and the matching the statement with the plurality of
comparative statements, are performed responsive to determining
that the statement does not match the information associated with
the domain.
18. The non-transitory computer readable storage medium of claim
13, further comprising performing a computer-implemented natural
language technique that classifies the question and determines the
domain.
19. The non-transitory computer readable storage medium of claim
13, further comprising performing a computer-implemented natural
language technique that parses the answer, extracts the plurality
of statements and identifies duplicate statements in the answer,
and annotates each of the plurality of statements as fact or
opinion.
20. The system of claim 1, wherein the cognitive engine invokes the
comparative assessment module for determining whether the statement
is accurate or inaccurate, responsive to determining that the
statement matches with a confidence that is below the accuracy
threshold.
21. The method of claim 6, wherein the searching of the database of
answers to the question and the matching the statement with the
plurality of comparative statements, are performed responsive to
determining that the statement matches with a confidence that is
below the accuracy threshold.
22. The non-transitory computer readable storage medium of claim
13, wherein the searching of the database of answers to the
question and the matching the statement with the plurality of
comparative statements, are performed responsive to determining
that the statement matches with a confidence that is below the
accuracy threshold.
Description
FIELD
[0001] The present application relates generally to computers and
computer applications, and more particularly to a
computer-implemented cognitive system that assesses subjective
question-answers.
BACKGROUND
[0002] Assessment of subjective content usually takes manual
processing. For example, assessing examination answer sheets with
subjective answers is mostly done manually while assessing
objective answers has been automated. Even when automated,
assessing subjective answers require a reference gold standard or
solution set for accurate assessment. The present disclosure in one
aspect describes a computer-implemented system and method that
assesses answers without an input solution set.
BRIEF SUMMARY
[0003] A computer-implemented cognitive system and method may be
provided. The system, in one aspect, may include one or more
hardware processors. A cognitive engine may be operable to execute
on one or more of the hardware processors and further operable to
receive first data representative of a domain associated with a
question. The cognitive engine may be further operable to search a
database of sources and retrieve information associated with the
domain. The cognitive engine may be further operable to receive
second data representative of an answer to the question, the second
data comprising a plurality of statements. The cognitive engine may
be further operable to determine whether a statement is accurate or
inaccurate, for each of the plurality of statements based on
matching the statement with the information associated with the
domain according to an accuracy threshold. A scoring module may be
operable to execute on one or more of the hardware processors and
further operable to determine an overall score for the answer based
on a number of statements determined to be accurate, a number of
statements determined to be inaccurate, a number of duplicate
statements in the answer relative to a total number of statements
in the answer. A visual assessment module may be operable to
generate a visual graphics representing accurate and inaccurate
statements determined by the cognitive engine and the overall
score. A graphical user interface may be operable to display the
visual graphics and interact with a user to allow the user to
modify the overall score.
[0004] A computer-implemented method of assessing a subjective
answer, in one aspect, may include receiving first data
representative of a domain associated with a question. The method
may also include receiving second data representative of an answer
to the question, the second data comprising a plurality of
statements. The method may also include searching a database of
sources to retrieve information associated with the domain. The
method may also include determining whether a statement is accurate
or inaccurate, for each of the plurality of statements based on
matching the statement with the information associated with the
domain according to an accuracy threshold. The method may also
include determining an overall score for the answer based on a
number of statements determined to be accurate, a number of
statements determined to be inaccurate, a number of duplicate
statements in the answer relative to a total number of statements
in the answer. The method may also include generating visual
graphics representing accurate and inaccurate statements and the
overall score. The method may also include displaying the visual
graphics on a display device.
[0005] A computer readable storage medium storing a program of
instructions executable by a machine to perform one or more methods
described herein also may be provided.
[0006] Further features as well as the structure and operation of
various embodiments are described in detail below with reference to
the accompanying drawings. In the drawings, like reference numbers
indicate identical or functionally similar elements.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIG. 1 is a diagram illustrating a cognitive system that
assesses subjective answers in one embodiment of the present
disclosure.
[0008] FIG. 2 is a flow diagram illustrating a computer-implemented
method that automatically assesses subjective answers in one
embodiment of the present disclosure.
[0009] FIG. 3 illustrates a schematic of an example computer or
processing system that may implement a cognitive system in one
embodiment of the present disclosure.
DETAILED DESCRIPTION
[0010] A computer-implemented cognitive system and method are
disclosed. Given a question and its essay-type answers, the
cognitive system and method of the present disclosure in one
embodiment can analyze and classify the question to determine a
domain of expertise and query its knowledge base to discover facets
of the domain of expertise. The cognitive system and method in one
embodiment compares the given answer with known facts and rates its
accuracy, e.g., confidence. The cognitive system and method in one
embodiment may use a comparative approach to determine the
accuracy, when facts are unknown or below a confidence threshold.
The cognitive system and method in one embodiment may also assign
an overall score to the input answer using relative scoring. A
graphical user interface (GUI) interface may also be provided for
assessing the scoring mechanism.
[0011] A system and/or method in one embodiment may automatically
evaluate subjective answers in the absence of any reference answers
or standards. The system and/or method in one embodiment may
automatically score these subjective answers based on the known
facts related to the domain by querying a cognitive engine. The
system and/or method in one embodiment may automatically score a
statement by comparing with similar statements in other answers, if
the confidence score of the related facts is below a threshold. The
system and/or method in one embodiment may automatically arrive at
a final score from the number of accurate, inaccurate and duplicate
statements using a reward and/or penalty approach. A visual
interface may be provided for post-processing the automatic
evaluations.
[0012] FIG. 1 is a diagram illustrating a cognitive system that
assesses subjective answers in one embodiment of the present
disclosure. The system in one embodiment may include the following
computer-implemented functions or modules that execute one or more
hardware processors (e.g., 102): named entity recognition 104,
paraphrase detection 106, facts/opinion recognition 108,
comparative assessment module 112, a fact and/or non-fact based
scoring functions 116, a cognitive engine 110 and visual assessment
module 118. One or more of these functions and modules may
implement information extraction, text analytics and/or natural
language processing techniques on a computer processor. The
components may execute or run on one or more hardware processors,
microprocessors, or computer processors 102. The hardware
processors may be arranged in a distributed manner, for example,
communicating over a computer communications network in running the
components shown in FIG. 1. In another aspect, the components may
run on a single processor.
[0013] A computer-executable entity recognition module 104 may
receive a question 124 and perform entity recognition. For example,
a question 124 may be retrieved from memory or storage device. As
another example, a question 124 may be received directly from a
user interface process that presented the question to a user to
answer. Entity Recognition detects concepts such as names of
people, places, companies, events, locations, etc. The entity
recognition module 104 may classify the question and determine one
or more domains associated with the question, e.g., the topic or
subject matter of the question.
[0014] A cognitive engine 110 that executes on one or more hardware
processors may receive the classified question and/or the
determined one or more domains (e.g., referred to as first data
representative of a domain associated with the question), and
retrieve facts or information associated with the domain from data
sources 122, for example, via a computer communication network. The
data sources 122 may include the information available on the
Internet, various databases and knowledge-bases. A search
engine-like processing coupled with a computer-implemented natural
language processing technique may be performed to retrieve
information or data associated with the questions or the domain of
the question.
[0015] A paraphrase detection module 106 receives an answer 126 to
the question 124 and parses the answer e.g., by executing a
computer-implemented natural language processing technique, into
paraphrases. In one embodiment, by only considering unique
paraphrases, duplicate statements in the answer can be eliminated
from the scoring, or duplicate words and/or phrases in the
statement can be highlighted to aid the processing in cognitive
engine 110. An answer 126 may be retrieved from memory or storage
device. As another example, an answer 126 may be received directly
from a user interface via which a user entered or input the
answer.
[0016] A facts and/or opinion recognition module 108 extracts facts
and/or opinions from the paraphrases. One or more natural language
processing techniques may be executed to extract facts and/or
opinions. For example, techniques that extract facts and/or
opinions may use Part-Of-Speech (POS) taggers to annotate syntax
such as nouns, verbs, adjectives, prepositions, noun phrases, etc.
Using such POS taggers, a statement can be classified as fact or
opinion. As an example, words and phrases such as "I think", "I
suspect", "That might be", "There could be" and so on increase the
possibility of the user opining, whereas phrases such as " . . . is
known to be . . . ", " . . . was the year of . . . ", "It started a
. . . " and so on, indicate that a fact is being stated. The
paraphrase detection module 106 and the facts and/or opinion
recognition module 108 may perform their respective processing for
each of the multiple answers.
[0017] Input to the cognitive engine 110, for example, may comprise
a topic (e.g., associated with the question referred to above as
first data representative of a domain associated with a question)
and a set of statements made in the answer (e.g., an essay), e.g.,
referred to as second data representative of an answer to the
question. The cognitive engine 110 receives the fact and/or opinion
statements extracted from the answer and compares those statements
associated with the answer with the information associated with the
question domain retrieved from the data sources 122. For each
extracted statement in the answer, the cognitive engine 110
determines whether the statement is accurate based on an accuracy
threshold. For example, based on the comparison of the statement
and retrieved information, and determination of how closely they
match (e.g., match up to a given threshold), whether the statement
is accurate or not, may be determined. For instance, a threshold
may be pre-defined and may be configurable. A threshold value, for
example, may be 90% matching. The cognitive engine 110 may also
assign several factual scores to each statement based on evidences
gathered from different data sources 122 and then combine them to
determine the final score. For instance, the factual score
determines whether each statement is a fact or not. If the
statement is an opinion, the more likely it is that the final score
of the statement decreases.
[0018] Responsive to determining that there is no matching
reference information that match the statement, the cognitive
engine 110 may invoke a comparative assessment module 112 that
finds similar statements made by other individuals and determines
the accuracy e.g., by searching a database of other answers 114.
For example, if it is determined that the cognitive engine's 110
assessment has below threshold level confidence, the statement may
be scored based on statements found in answers (e.g., essays) given
by other individuals (e.g., students who answered the same
question). For example, if many students have given the same or
similar statement then it is highly likely that the statement is a
fact. For example, the comparative assessment module 112 may search
its database of answers 114 given by other individuals and find
matching statements. In another aspect, the comparative assessment
module 112 may search the database of answers 114 and provide a
plurality of comparative statements in the database of answers to
the cognitive engine 110, and the cognitive engine 110 determines
the degree of similarly between the statement in the answer and the
plurality of comparative statements. Based on this comparative
assessment of whether the statement matches with those statements
given by other individuals and to what degree, the cognitive engine
110 may assign a factual score to each statement that the
comparative assessment module 112 assessed.
[0019] In another aspect, the cognitive engine 110 may utilize both
the data source information 122 and the comparative data from the
comparative assessment module 112 to determine whether a statement
is accurate or inaccurate, and/or to assign an accuracy score to
the statement.
[0020] In one aspect, the information retrieved from data sources
122 may have associated confidence scores. For instance, a data
source may be classified as highly reliable and/or trustworthy. In
such a scenario, the cognitive engine 110 may assign a confidence
of 1.0 (i.e. 100%) to all the facts extracted from that data
source. The cognitive engine 110 can assign this confidence at the
time of ingesting such a data source. Similarly, based on the
degree of reliability of data sources, information from such data
sources may be assigned different confidence levels. The cognitive
engine 110 may also invoke the comparative assessment module 112,
e.g., if the matching information has associated confidence score
that is below a defined threshold value.
[0021] Based on the cognitive engine's and/or comparative
assessment module's accuracy determination of the statements in the
answer, a scoring module 116 determines the number of accurate
statements, the number of inaccurate statements, and the number of
duplicate statements made relative to the overall number of
statements. The scoring module 116 determines an overall score for
the answer, for example, based on the number of accurate
statements, the number of inaccurate statements, and the number of
duplicate statements made relative to the overall number of
statements. The scoring module 116, for example, scores each answer
(e.g., essay) based on scores assigned to each statement in the
answer. The scoring module 116 may determine the overall score with
penalties for inaccurate and duplicate facts and rewards for
accurate statements (hits).
[0022] A visual assessment module 118 generates a visual assessment
of the statements in the answer, for example, Red Amber Green (RAG)
assessment of the statements, and presents or displays the
assessment visually on a display device 120, for example, via
graphical user interface. The visual assessment module 118 via the
graphical user interface may allow a user to correct and/or
override the scores assigned by the cognitive engine 110. The
modified score, for example, may be used to improve the cognitive
engine 110, for example, to allow the cognitive engine 110 to
learn, for example, by machine learning.
[0023] FIG. 2 is a flow diagram illustrating a computer-implemented
method that automatically assesses subjective answers in one
embodiment of the present disclosure. One or more hardware
processors, microprocessors, or computer processors may execute or
implement the method shown in FIG. 2. A question may be received
and at 202, entity recognition for the question is performed. The
question is classified and relevant facts are fetched for the
domain. Entity Recognition detects concepts such as names of
people, places, companies, events, locations, and/or others. Based
on such extracted concepts, relevant domain facts obtained by the
cognitive engine, after ingestion and processing of data sources,
can then be fetched and loaded.
[0024] An answer to the question may be received and at 204, the
answer is parsed. Paraphrase detection is performed on the answer
that is parsed, duplicate statements are identified and facts
and/or opinions in the answer are extracted. One or more natural
language processing techniques may be executed to identify
duplicate statements and extract facts and/or opinions. These
techniques may use Part-Of-Speech (POS) taggers to annotate syntax
such as nouns, verbs, adjectives, prepositions, noun phrases, etc.,
using which a statement can be classified as fact or opinion. As an
example, words and phrases such as "I think", "I suspect", "That
might be", "There could be" and so on increase the possibility of
the user opining, whereas phrases such as " . . . is known to be .
. . ", " . . . was the year of . . . ", "It started a . . . " and
so on, indicate that a fact is being stated. Multiple answers may
be received and the processing shown in FIG. 2 may be performed for
each of the multiple answers.
[0025] At 206, for an extracted statement (fact or opinion)
extracted at 204, its accuracy (accuracy score) is determined based
on an accuracy threshold, e.g., by looking up or searching
cognitive engine's data sources, for example, as references as well
as the inherent confidence, e.g., a fact scores high on confidence
than an opinion that the user expresses. The processing at 206 in
one embodiment is performed for all extracted statements.
[0026] At 208, if no matching reference is found or if the
confidence score of the reference is below the accuracy threshold,
a comparative approach is performed to find similar statements made
by other individuals and the accuracy of the statement is
determined based on the comparative approach.
[0027] At 210, for an answer, the number of accurate statements
determined to be accurate according to a threshold, the number of
inaccurate statements determined to be not accurate according to
the threshold, and the number of duplicate statements made relative
to the overall number of statements, are determined.
[0028] At 212, an overall score for an answer is determined based
on the attributes determined at 210. The overall score may be
determined with penalties for inaccurate and duplicate facts and
rewards for accurate statements (hits).
[0029] At 214, a visual assessment of the statements in an answer
may be presented or displayed on a display device, for example, as
a visual or graphical user interface. An example of such visual
assessment may include Red Amber Green (RAG) assessment of the
statements in a visual interface.
[0030] The following illustrates an example question, answer and an
assessment of the answer in one embodiment of the present
disclosure. Consider an example question: "Describe the Great
Depression." An example answer given may be as follows: The Great
Depression started in US around 1930. It caused lot of jobs to be
lost, increase in poverty and unemployment, and even led to stock
market crash. It affected several economies worldwide and ended
with World War 2." The answer is parsed into paraphrases and
duplicate statements, if any, may be identified. Fact and/or
opinion statements are extracted from the answer.
[0031] Column 1 of Table 1 below illustrates example statements
extracted from the answer. These statements are input to the
cognitive engine in one embodiment.
[0032] Column 2 of Table 1 below illustrates confidence level
associated with the extracted statements. A fact scores high on
confidence than an opinion that the user expresses. For example,
the last two rows have an input confidence score of 1.0 as they are
classified as `facts` by the facts and/or opinion recognition
module 108. The first row is classified as `opinion` due to the
presence of words/phrases such as "around". This leads the
cognitive engine 110 to decrease the input confidence of the
statement, which in turn affects the final statement score. The
second statement is identified as containing duplicate
words/phrases--"lot of jobs to be lost" and "unemployment"--by the
paraphrase detection module 106. This leads the cognitive engine
110 to decrease the input confidence of the statement, which in
turn affects the final score of the statement.
[0033] Column 3 of Table 1 below illustrates example information
retrieved from example sources based on a determined domain of the
question. For instance, the question may be classified and its
domain determined as "history" and "history of US" and "Great
Depression." Data sources may be searched to find information
associated with that domain, for example, using search engine-like
techniques coupled with natural language processing techniques.
Examples of data sources may include database sources available on
the World Wide Web (Web), for example, crowd sourced encyclopedia
database (e.g., Wikipedia) or the like, a database of historical
information (e.g., history.com) or the like, and/or other available
and/or accessible data sources. Sources may also include
comparative statements from other individuals (e.g., shown in the
last row of Table 1).
[0034] Column 4 of Table 1 below illustrates confidence value
associated with the source information. Column 5 of Table 1 below
illustrates statement score determined, for example, by comparing
the answer statement with database sources and/or comparative
answers by other individuals, and taking into consideration the
input confidence score (e.g., intermediate score), for example, as
described above.
TABLE-US-00001 Input Source Statement Input Conf. Source Conf.
Score The Great Depression 0.7 On-line encyclopedia: The depression
1.0 0.8 started in US around originated in the U.S., after the fall
in 1930. stock prices that began around Sep. 4, 1929. It caused lot
of jobs to 0.9 On-line history information web site: As 1.0 0.9 be
lost, increase in consumer confidence vanished in the poverty and
wake of the stock market crash, the unemployment, and downturn in
spending and investment led even led to stock factories and other
businesses to slow market crash. down production and construction
and begin firing their workers. For those who were lucky enough to
remain employed, wages fell and buying power decreased. Many
Americans forced to buy on credit fell into debt, and the number of
foreclosures and repossessions climbed steadily. It affected
several 1.0 On-line history information web site: The 1.0 1.0
economies worldwide. adherence to the gold standard, which joined
countries around the world in a fixed currency exchange, helped
spread the Depression from the United States throughout the world,
especially in Europe. It ended with World 1.0 Comparative: 0.9 War
2. [. . .] economy turned around with advent 1.0 of second World
war [. . .] [. . .] Until Hitler rose to power and Pearl 1.0 Harbor
attack in 1941, [. . .]
[0035] FIG. 3 illustrates a schematic of an example computer or
processing system that may implement a cognitive system in one
embodiment of the present disclosure. The computer system is only
one example of a suitable processing system and is not intended to
suggest any limitation as to the scope of use or functionality of
embodiments of the methodology described herein. The processing
system shown may be operational with numerous other general purpose
or special purpose computing system environments or configurations.
Examples of well-known computing systems, environments, and/or
configurations that may be suitable for use with the processing
system shown in FIG. 3 may include, but are not limited to,
personal computer systems, server computer systems, thin clients,
thick clients, handheld or laptop devices, multiprocessor systems,
microprocessor-based systems, set top boxes, programmable consumer
electronics, network PCs, minicomputer systems, mainframe computer
systems, and distributed cloud computing environments that include
any of the above systems or devices, and the like.
[0036] The computer system may be described in the general context
of computer system executable instructions, such as program
modules, being executed by a computer system. Generally, program
modules may include routines, programs, objects, components, logic,
data structures, and so on that perform particular tasks or
implement particular abstract data types. The computer system may
be practiced in distributed cloud computing environments where
tasks are performed by remote processing devices that are linked
through a communications network. In a distributed cloud computing
environment, program modules may be located in both local and
remote computer system storage media including memory storage
devices.
[0037] The components of computer system may include, but are not
limited to, one or more processors or processing units 12, a system
memory 16, and a bus 14 that couples various system components
including system memory 16 to processor 12. The processor 12 may
include cognitive system modules 10 that performs the methods
described herein. The modules 10 may be programmed into the
integrated circuits of the processor 12, or loaded from memory 16,
storage device 18, or network 24 or combinations thereof.
[0038] Bus 14 may represent one or more of any of several types of
bus structures, including a memory bus or memory controller, a
peripheral bus, an accelerated graphics port, and a processor or
local bus using any of a variety of bus architectures. By way of
example, and not limitation, such architectures include Industry
Standard Architecture (ISA) bus, Micro Channel Architecture (MCA)
bus, Enhanced ISA (EISA) bus, Video Electronics Standards
Association (VESA) local bus, and Peripheral Component
Interconnects (PCI) bus.
[0039] Computer system may include a variety of computer system
readable media. Such media may be any available media that is
accessible by computer system, and it may include both volatile and
non-volatile media, removable and non-removable media.
[0040] System memory 16 can include computer system readable media
in the form of volatile memory, such as random access memory (RAM)
and/or cache memory or others. Computer system may further include
other removable/non-removable, volatile/non-volatile computer
system storage media. By way of example only, storage system 18 can
be provided for reading from and writing to a non-removable,
non-volatile magnetic media (e.g., a "hard drive"). Although not
shown, a magnetic disk drive for reading from and writing to a
removable, non-volatile magnetic disk (e.g., a "floppy disk"), and
an optical disk drive for reading from or writing to a removable,
non-volatile optical disk such as a CD-ROM, DVD-ROM or other
optical media can be provided. In such instances, each can be
connected to bus 14 by one or more data media interfaces.
[0041] Computer system may also communicate with one or more
external devices 26 such as a keyboard, a pointing device, a
display 28, etc.; one or more devices that enable a user to
interact with computer system; and/or any devices (e.g., network
card, modem, etc.) that enable computer system to communicate with
one or more other computing devices. Such communication can occur
via Input/Output (I/O) interfaces 20.
[0042] Still yet, computer system can communicate with one or more
networks 24 such as a local area network (LAN), a general wide area
network (WAN), and/or a public network (e.g., the Internet) via
network adapter 22. As depicted, network adapter 22 communicates
with the other components of computer system via bus 14. It should
be understood that although not shown, other hardware and/or
software components could be used in conjunction with computer
system. Examples include, but are not limited to: microcode, device
drivers, redundant processing units, external disk drive arrays,
RAID systems, tape drives, and data archival storage systems,
etc.
[0043] 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.
[0044] 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.
[0045] 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.
[0046] 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 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.
[0047] 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.
[0048] 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.
[0049] 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.
[0050] 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.
[0051] The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the invention. As used herein, the singular forms "a", "an" and
"the" are intended to include the plural forms as well, unless the
context clearly indicates otherwise. It will be further understood
that the terms "comprises" and/or "comprising," when used in this
specification, specify the presence of stated features, integers,
steps, operations, elements, and/or components, but do not preclude
the presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof.
[0052] The corresponding structures, materials, acts, and
equivalents of all means or step plus function elements, if any, in
the claims below are intended to include any structure, material,
or act for performing the function in combination with other
claimed elements as specifically claimed. The description of the
present invention has been presented for purposes of illustration
and description, but is not intended to be exhaustive or limited to
the invention in the form disclosed. Many modifications and
variations will be apparent to those of ordinary skill in the art
without departing from the scope and spirit of the invention. The
embodiment was chosen and described in order to best explain the
principles of the invention and the practical application, and to
enable others of ordinary skill in the art to understand the
invention for various embodiments with various modifications as are
suited to the particular use contemplated.
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