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I
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d
b
y
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ed
ia
p
latf
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r
m
s
[
1
]
,
[
2
]
.
B
ey
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n
d
s
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v
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g
as
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tim
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[
3
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,
[
4
]
.
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r
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s
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tim
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s
ac
cu
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an
d
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[
5
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–
[
7
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.
User
s
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in
ter
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s
[
8
]
,
[
9
]
.
Mo
r
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eth
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ty
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ased
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ML
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p
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f
s
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co
m
m
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n
icatio
n
[
1
0
]
,
[
1
1
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
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I
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J
R
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&
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to
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I
SS
N:
2722
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2
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S
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esp
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[
1
2
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[
1
3
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As
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tr
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[
1
4
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,
[
1
5
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.
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[
1
6
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[
1
8
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I
n
2
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2
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a
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[
1
9
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r
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ar
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r
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I
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2
0
2
3
,
Har
ita
[
2
1
]
cr
ea
ted
an
en
d
-
to
-
e
n
d
s
y
s
tem
th
at
ca
n
p
r
ed
ict
th
e
s
en
tim
en
t
o
f
a
co
llectio
n
o
f
twee
ts
an
d
th
e
p
r
ice
o
f
B
itco
i
n
b
ased
o
n
th
e
s
en
tim
en
t p
r
ed
ict
io
n
.
I
n
2
0
2
3
,
Go
th
an
e
et
a
l.
[
2
2
]
p
r
o
v
id
ed
a
d
ee
p
lear
n
i
n
g
(
DL
)
m
o
d
el
to
d
etec
t
th
e
d
eg
r
ee
o
f
p
o
la
r
ity
in
T
wi
tter
p
o
s
tin
g
s
.
T
h
is
ap
p
r
o
ac
h
i
m
p
r
o
v
es
p
er
f
o
r
m
an
ce
b
y
8
1
%
ac
cu
r
ac
y
r
a
n
g
in
g
f
r
o
m
5
4
to
5
9
%.
I
n
2
0
2
4
,
Nee
lak
an
d
an
et
a
l.
[
2
3
]
p
r
o
v
id
ed
a
p
r
o
f
icien
t
SA
tech
n
iq
u
e
in
T
witter
d
ata
p
er
f
o
r
m
ed
th
e
b
est r
eg
ar
d
in
g
r
ec
all,
ac
cu
r
ac
y
,
F
-
s
co
r
e
,
an
d
p
r
ec
is
io
n
.
I
n
2
0
2
4
,
Z
h
ao
et
a
l.
[
2
4
]
s
u
g
g
ested
a
tr
an
s
f
o
r
m
er
an
d
lex
i
co
n
-
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ased
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T
L
SA)
f
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ac
cu
r
ate
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tr
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E
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tex
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m
en
d
e
d
p
r
ac
tices
f
o
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ac
cu
r
ate
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d
tr
u
s
two
r
th
y
SA.
I
n
2
0
2
5
,
Aziz
et
a
l.
[
2
5
]
p
r
o
v
id
e
d
a
u
n
i
f
ied
ar
ch
itectu
r
e
o
f
m
u
ltimo
d
a
l tr
an
s
f
o
r
m
er
s
f
u
s
io
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f
o
r
d
esir
e,
em
o
tio
n
,
a
n
d
SA
(
MM
T
F
-
DE
S)
m
o
d
el
f
o
r
th
e
m
u
ltimo
d
al
h
u
m
an
d
esire
u
n
d
er
s
tan
d
in
g
ch
allen
g
e.
T
h
is
tech
n
iq
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e
p
e
r
f
o
r
m
s
2
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2
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etter
f
o
r
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o
tio
n
an
aly
s
is
.
I
n
2
0
2
5
,
B
r
u
n
et
a
l.
[
2
6
]
d
is
co
v
er
ed
th
at
th
e
e
m
o
tio
n
-
s
en
s
itiv
e
ch
atb
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t
was
p
er
ce
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as
m
o
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m
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tr
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s
two
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e
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s
er
f
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p
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with
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em
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ch
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o
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s
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itiv
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o
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s
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etter
ex
p
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ce
with
a
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ally
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en
s
itiv
e
ch
atb
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t
th
an
with
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n
e
th
at
is
em
o
tio
n
ally
in
s
en
s
itiv
e.
I
n
2
0
2
5
,
Ab
in
ay
a
et
a
l.
[
1
3
]
s
u
g
g
este
d
a
n
o
v
el
h
y
b
r
id
c
h
atb
o
t
s
y
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n
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ed
tex
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m
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tio
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B
E
R
T
C
NN
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r
k
(
T
E
B
C
-
Net)
,
wh
ich
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ter
p
r
ets
u
s
er
em
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tio
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d
p
r
o
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ce
s
m
o
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wer
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m
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is
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k
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C
NN)
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o
d
el
th
at
h
as
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ee
n
p
ar
ticu
lar
ly
tr
ain
ed
f
o
r
em
o
tio
n
r
ec
o
g
n
itio
n
an
aly
ze
s
th
e
p
r
o
c
ess
ed
im
ag
e
an
d
ass
ig
n
s
p
r
o
b
ab
ilit
ies
to
v
ar
io
u
s
e
m
o
tio
n
s
,
ac
h
iev
in
g
7
4
.
1
4
%
ac
cu
r
ac
y
.
Ad
d
itio
n
ally
,
ch
alle
n
g
es
lik
e
a
lack
o
f
s
ca
lab
ilit
y
,
ab
s
en
ce
o
f
in
ter
ac
tiv
e
q
u
esti
o
n
in
g
an
d
ch
atb
o
t
ass
is
tan
ce
ar
e
th
e
cr
itical
lim
itatio
n
s
.
T
o
tack
le
th
ese
p
r
o
b
lem
s
a
n
ew
I
C
h
at
-
AI
m
et
h
o
d
o
lo
g
y
h
as
b
ee
n
s
u
g
g
ested
f
o
r
s
en
tim
en
t
-
awa
r
e
ch
atb
o
t
i
n
ter
ac
tio
n
.
T
h
e
k
ey
o
b
jectiv
es
o
f
th
e
d
ev
elo
p
ed
I
C
h
at
-
AI
h
av
e
b
ee
n
g
iv
en
as
f
o
llo
ws
:
i)
T
h
e
k
ey
o
b
jectiv
e
o
f
th
is
wo
r
k
is
to
e
n
h
an
ce
u
s
er
in
ter
ac
ti
o
n
b
y
in
t
eg
r
atin
g
s
en
tim
en
t
an
aly
s
is
in
to
ch
atb
o
t
c
o
n
v
e
r
s
atio
n
s
u
s
in
g
a
m
u
lti
-
ag
e
n
t
ar
ch
itectu
r
e;
ii)
T
h
e
p
r
o
p
o
s
e
d
m
eth
o
d
em
p
l
o
y
s
wo
r
d
2
v
ec
(
W
2
V)
,
b
ag
o
f
wo
r
d
s
(
B
o
W
)
,
an
d
ter
m
f
r
eq
u
e
n
c
y
–
in
v
er
s
e
d
o
cu
m
en
t
f
r
eq
u
e
n
c
y
(
T
F
-
I
DF)
m
o
d
els
f
o
r
f
ea
tu
r
e
ex
tr
ac
tio
n
,
ef
f
ec
tiv
ely
co
n
v
e
r
tin
g
tex
t
u
al
d
a
ta
in
to
n
u
m
e
r
ical
r
ep
r
esen
ta
tio
n
s
f
o
r
ac
cu
r
ate
s
en
tim
en
t
class
if
icat
io
n
;
iii)
T
h
e
p
r
o
p
o
s
ed
I
C
h
at
-
AI
m
o
d
el
u
tili
ze
s
a
d
ee
p
Kr
o
n
ec
k
er
n
eu
r
al
n
etwo
r
k
(
DKNN
)
f
o
r
s
en
tim
en
t
class
if
icatio
n
,
ca
teg
o
r
izin
g
e
m
o
tio
n
s
in
to
s
ad
,
h
ap
p
y
,
n
eu
tr
al,
f
ea
r
f
u
l,
an
d
an
g
r
y
f
o
r
p
r
ec
is
e
s
en
tim
en
t
id
e
n
tific
atio
n
;
iv
)
T
h
e
p
r
o
p
o
s
ed
f
r
a
m
ewo
r
k
in
c
o
r
p
o
r
ates
an
in
ter
ac
tio
n
lay
er
th
at
e
n
ab
les
s
ca
lab
le
an
d
p
er
s
o
n
alize
d
co
n
v
er
s
atio
n
s
ac
r
o
s
s
d
iv
er
s
e
p
latf
o
r
m
s
;
an
d
v
)
T
h
e
p
er
f
o
r
m
a
n
c
e
o
f
th
e
d
ev
elo
p
ed
I
C
h
at
-
AI
ap
p
r
o
a
ch
is
ev
alu
ated
u
s
in
g
k
ey
p
ar
am
eter
s
in
clu
d
in
g
ac
c
u
r
ac
y
,
p
r
ec
is
io
n
,
r
ec
all,
F1
-
s
co
r
e,
ex
ec
u
tio
n
tim
e,
t
h
r
o
u
g
h
p
u
t,
co
m
p
lex
ity
,
er
r
o
r
r
ate,
s
ca
lab
ilit
y
,
an
d
r
esp
o
n
s
e
tim
e.
T
h
e
r
est
o
f
t
h
e
s
u
g
g
ested
ap
p
r
o
ac
h
ar
e
p
r
o
v
id
ed
as
f
o
llo
ws.
Sectio
n
2
o
f
f
e
r
s
a
liter
at
u
r
e
s
u
r
v
ey
.
Sectio
n
3
p
r
o
v
id
es
th
e
s
u
g
g
ested
I
C
h
at
-
AI
tech
n
iq
u
e.
Sectio
n
4
d
etails
th
e
f
in
d
in
g
s
an
d
d
i
s
cu
s
s
io
n
.
Sectio
n
5
ex
p
lain
s
th
e
co
n
cl
u
s
io
n
.
2.
P
RO
P
O
SE
D
SYS
T
E
M
I
n
th
is
s
ec
tio
n
,
a
n
o
v
el
in
ter
ac
tiv
e
C
h
atb
o
t
with
Gen
-
AI
(
I
C
h
at
-
AI
)
a
p
p
r
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ac
h
h
as
b
ee
n
p
r
o
p
o
s
ed
f
o
r
s
en
tim
en
t
-
awa
r
e
ch
atb
o
t
in
te
r
ac
tio
n
.
I
n
itially
,
th
e
r
aw
d
ata
ar
e
g
ath
e
r
ed
f
r
o
m
t
h
e
d
atab
ase.
Fig
u
r
e
1
s
h
o
ws
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e
p
r
o
p
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s
ed
I
C
h
at
-
AI
f
r
am
e
wo
r
k
.
2
.
1
.
Da
t
a
c
o
llect
io
n
T
h
e
p
r
o
ce
d
u
r
e
c
o
m
m
en
ce
s
with
r
aw,
u
n
s
tr
u
ctu
r
e
d
tex
t
d
ata.
T
h
is
co
u
ld
in
clu
d
e
twee
ts
,
p
r
o
d
u
ct
r
ev
iews,
co
n
s
u
m
er
f
ee
d
b
ac
k
,
co
m
m
en
ts
o
n
s
o
cial
m
ed
ia,
an
d
s
o
o
n
.
T
h
e
in
f
o
r
m
atio
n
is
ac
cu
m
u
lated
f
r
o
m
a
v
ar
iety
o
f
s
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u
r
ce
s
,
co
m
p
r
is
in
g
s
o
cial
m
ed
ia
p
latf
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r
m
s
,
web
s
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cu
s
to
m
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s
u
r
v
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,
an
d
m
o
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2
.
2
.
Da
t
a
pre
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pro
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s
s
ing
Pre
-
p
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s
s
in
g
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n
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tial
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tep
in
tex
t
an
aly
s
is
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at
p
r
e
p
ar
es
d
ata
f
o
r
f
u
r
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s
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Sto
p
wo
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d
s
ar
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s
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E
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lis
h
wo
r
d
s
th
at
d
o
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'
t
co
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tr
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te
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SA.
T
h
e
s
tem
m
in
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elp
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elim
in
ate
Evaluation Warning : The document was created with Spire.PDF for Python.
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209
202
u
n
n
ec
ess
ar
y
wo
r
d
c
o
m
p
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tatio
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b
y
co
n
v
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g
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ar
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u
s
wo
r
d
ten
s
es
in
to
th
eir
m
o
s
t
b
asic
f
o
r
m
.
C
o
m
b
in
in
g
two
o
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m
o
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e
wo
r
d
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in
to
a
s
in
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w
o
r
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k
n
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atiza
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T
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k
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izatio
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ass
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e
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u
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d
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1
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tili
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eth
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p
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M
ulti
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ing
la
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T
h
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er
in
clu
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es
s
en
tim
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n
t
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aly
s
is
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en
g
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t
tr
ac
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d
a
s
u
m
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ar
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en
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e
s
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tim
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aly
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is
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d
o
n
e
b
y
th
e
u
s
e
o
f
DKNN
,
wh
ich
class
if
ies
th
e
em
o
tio
n
s
in
to
s
ad
,
h
a
p
p
y
,
n
eu
t
r
al,
f
ea
r
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u
l,
a
n
d
an
g
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h
en
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e
n
g
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e
n
t
tr
ac
k
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m
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ito
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th
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s
u
m
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ar
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ar
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er
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ter
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m
o
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u
les
ar
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ex
p
licitly
ex
p
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ed
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elo
w.
2
.
4
.
1
.
Sentim
ent
a
na
ly
s
is
cla
s
s
if
ica
t
io
n us
i
ng
DK
NN
T
h
is
wo
r
k
u
s
es
DKNN
to
cla
s
s
if
y
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o
tio
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f
o
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p
r
o
v
in
g
ac
cu
r
ac
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in
h
ig
h
-
d
im
en
s
io
n
al
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ata.
W
e
ac
tu
ally
u
tili
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th
e
KDNN
to
m
eth
o
d
(
|
)
th
e
s
tate's
p
o
s
ter
io
r
p
r
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b
ab
ilit
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g
iv
en
th
e
o
b
s
er
v
ati
o
n
v
ec
to
r
.
Fig
u
r
e
2
d
is
p
lay
s
th
e
ar
ch
itec
tu
r
e
d
iag
r
a
m
o
f
t
h
e
DKNN
ap
p
r
o
ac
h
.
Fig
u
r
e
2
.
Ar
c
h
itectu
r
e
o
f
DKNN
m
o
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el
a.
DK
NN
cla
s
s
if
ica
t
io
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pro
ce
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p
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p
tim
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v
ec
to
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u
s
in
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s
co
r
in
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cr
iter
io
n
.
T
h
e
r
o
u
tin
g
p
r
o
ce
s
s
with
DKNN
p
r
o
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ed
s
as f
o
llo
ws
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
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2
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2
2
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204
−
T
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O
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ass
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ep
en
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t o
b
s
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ea
t
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e
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ch
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ith
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tes
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u
b
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s
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g
th
e
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o
v
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eq
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atio
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.
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h
e
o
u
tp
u
t
v
ec
to
r
with
th
e
h
ig
h
est
p
r
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a
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ilit
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o
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en
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e
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lass
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icat
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n
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ased
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icat
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ap
p
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o
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im
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v
es
th
e
p
r
ec
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io
n
o
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s
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r
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ictio
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,
wh
ich
en
s
u
r
es
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m
o
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eliab
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n
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er
s
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d
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g
o
f
u
s
er
o
p
in
io
n
s
.
Fin
ally
,
th
is
DKNN
m
o
d
el
clas
s
if
ies
th
e
em
o
tio
n
s
in
to
f
iv
e
ca
teg
o
r
ies s
u
ch
as sad
,
n
eu
tr
al,
f
ea
r
f
u
l,
h
a
p
p
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d
an
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.
2
.
4
.
2
.
E
ng
a
g
em
ent
t
ra
c
k
er
T
h
e
en
g
ag
e
m
en
t
an
aly
s
is
ag
en
t
tr
ac
k
s
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s
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ter
ac
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eh
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io
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lik
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lik
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s
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ar
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r
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n
s
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an
d
o
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er
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n
g
ag
e
m
en
t
m
etr
ics
f
r
o
m
s
o
cial
m
e
d
ia
p
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o
r
m
s
.
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h
e
ag
en
t
ap
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e
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ies
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aly
s
is
an
d
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o
m
aly
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eth
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s
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en
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atter
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at
in
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icate
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is
is
in
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ak
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en
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en
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with
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eter
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i
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e
if
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ativ
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in
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to
p
o
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t b
u
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ts
.
2
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4
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3
.
Su
m
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ent
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co
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m
en
t
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u
m
m
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izatio
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ag
en
t
ap
p
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tr
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tiv
e
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d
a
b
s
tr
ac
tiv
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u
m
m
ar
izatio
n
tech
n
iq
u
es
to
s
h
o
r
ten
len
g
th
y
u
s
er
co
m
m
en
ts
in
to
co
n
cise,
in
f
o
r
m
ativ
e
s
u
m
m
ar
ies
with
th
e
m
o
s
t
im
p
o
r
tan
t
s
en
tim
en
t
an
d
p
o
in
ts
.
T
h
e
s
u
m
m
ar
izatio
n
p
r
o
ce
d
u
r
e
is
b
ased
o
n
s
en
tim
en
t
-
ca
r
r
y
in
g
s
en
ten
ce
s
an
d
asp
ec
t
-
r
elate
d
co
n
ten
t
s
o
th
at
th
e
m
o
s
t im
p
o
r
tan
t c
o
n
te
n
t is p
r
eser
v
ed
in
th
e
s
u
m
m
ar
y
.
2
.
5
.
I
nte
ra
ct
i
o
n
la
y
er
T
h
e
in
ter
ac
tio
n
lay
er
s
er
v
es
as
th
e
co
m
m
u
n
icatio
n
lin
k
b
etwe
en
th
e
ch
atb
o
t
s
y
s
tem
an
d
its
en
d
-
u
s
er
s
.
Fo
llo
w
-
o
n
q
u
esti
o
n
s
o
r
f
u
r
th
er
q
u
esti
o
n
s
s
ee
k
in
g
clar
i
f
icatio
n
m
ay
b
e
ask
ed
with
o
u
t
r
estatem
en
t
o
f
t
h
e
o
r
ig
in
al
q
u
esti
o
n
b
y
t
h
e
u
s
er
s
wh
ile
en
g
ag
in
g
with
th
e
s
y
s
tem
th
r
o
u
g
h
th
e
ch
atb
o
t
i
n
ter
f
ac
e.
T
h
e
ch
atb
o
t
is
a
g
am
e
-
ch
an
g
er
in
th
e
u
s
er
ex
p
er
ien
ce
with
s
en
tim
en
t
an
al
y
s
is
d
ata.
I
n
s
tead
o
f
h
av
in
g
t
o
d
ig
th
r
o
u
g
h
s
tatic
d
ash
b
o
ar
d
s
o
r
tem
p
lated
r
e
p
o
r
ts
to
lo
ca
te
d
ata,
u
s
er
s
ca
n
s
im
p
ly
ask
q
u
esti
o
n
s
in
n
atu
r
a
l
lan
g
u
ag
e
an
d
g
et
in
s
tan
t,
co
n
tex
tu
ally
r
elev
an
t
r
esp
o
n
s
es.
W
ith
th
e
g
u
id
ed
e
x
p
lo
r
atio
n
ap
p
r
o
ac
h
,
t
h
e
u
s
er
s
ca
n
f
in
d
r
ele
v
an
t
f
in
d
in
g
s
th
e
y
wo
u
ld
n
o
t h
a
v
e
r
eq
u
ested
co
n
s
cio
u
s
ly
.
3.
RE
SU
L
T
S
AND
D
I
SCU
SS
I
O
N
I
n
th
is
s
ec
tio
n
,
th
e
s
u
g
g
ested
I
C
h
at
-
AI
f
r
am
ewo
r
k
is
i
m
p
lem
en
ted
in
a
Py
th
o
n
s
im
u
lato
r
.
T
o
ex
am
in
e
th
e
p
er
f
o
r
m
a
n
ce
o
f
t
h
e
d
ev
el
o
p
ed
I
C
h
at
-
AI
f
r
am
e
wo
r
k
,
it
h
as
b
ee
n
co
m
p
ar
ed
w
ith
o
th
er
tech
n
iq
u
es,
in
clu
d
in
g
R
o
B
E
R
T
a
[
1
9
]
,
T
L
SA
[
2
4
]
,
an
d
MM
T
F
-
DE
S [
2
5
]
.
A
n
u
m
b
er
o
f
im
p
o
r
tan
t
e
f
f
ic
ac
y
k
e
y
p
ar
am
eter
s
in
clu
d
in
g
r
e
ca
ll,
ex
ec
u
tio
n
ti
m
e,
co
m
p
lex
ity
,
F1
-
s
co
r
e,
p
r
ec
is
io
n
,
s
ca
lab
ilit
y
,
ac
cu
r
ac
y
,
an
d
r
esp
o
n
s
e
tim
e
wer
e
ev
alu
ated
to
d
eter
m
in
e
h
o
w
well
th
e
I
C
h
at
-
AI
m
eth
o
d
p
er
f
o
r
m
ed
.
3
.
1
.
Da
t
a
s
et
des
cr
iptio
n
I
n
th
is
wo
r
k
,
th
e
Go
E
m
o
tio
n
s
d
ataset
h
as
b
ee
n
u
tili
ze
d
.
T
h
e
Go
E
m
o
tio
n
s
d
ataset
is
a
co
r
p
u
s
o
f
5
8
k
R
ed
d
it
co
m
m
en
ts
m
an
u
ally
cl
ass
if
ied
b
y
h
u
m
an
s
in
to
2
8
d
i
f
f
er
en
t
em
o
tio
n
ca
teg
o
r
ies.
T
h
e
f
o
llo
win
g
lis
t
o
f
em
o
tio
n
s
is
o
r
g
an
ized
in
to
d
if
f
er
en
t
ca
te
g
o
r
ies:
am
u
s
em
e
n
t,
ca
r
in
g
,
l
o
v
e,
r
elief
,
n
er
v
o
u
s
n
ess
,
ex
citem
en
t,
cu
r
io
s
ity
,
s
u
r
p
r
is
e,
ap
p
r
o
v
al,
g
r
atitu
d
e,
f
ea
r
,
d
is
ap
p
r
o
v
al,
g
r
ief
,
jo
y
,
p
r
id
e,
d
is
ap
p
o
in
tm
e
n
t,
an
g
e
r
,
r
e
m
o
r
s
e,
s
ad
n
ess
,
r
ea
lizatio
n
,
d
esire
,
o
p
tim
is
m
,
em
b
ar
r
ass
m
en
t,
d
is
g
u
s
t,
co
n
f
u
s
io
n
,
a
d
m
ir
atio
n
,
an
d
an
n
o
y
a
n
ce
.
As
s
h
o
wn
in
Fig
u
r
e
3
,
we
will
b
e
im
p
lem
en
tin
g
th
e
f
u
n
d
am
en
tal
C
h
atb
o
t
c
o
n
f
ig
u
r
atio
n
in
to
p
r
ac
tice
to
m
ak
e
s
u
r
e
th
at
th
e
s
am
e
b
o
t
m
ay
b
e
u
tili
ze
d
to
o
f
f
er
v
ar
io
u
s
s
er
v
ices.
T
h
e
f
u
n
d
am
en
tal
s
etu
p
ca
n
b
e
ch
an
g
ed
to
s
u
it
a
g
iv
en
s
itu
atio
n
b
ased
o
n
th
e
n
ee
d
s
an
d
d
em
an
d
s
o
f
th
e
u
s
er
.
T
h
e
s
er
v
ice
m
an
ag
es
u
s
er
r
eq
u
ests
an
d
in
q
u
ir
ies s
u
ch
th
a
t r
esp
o
n
s
es a
r
e
d
y
n
am
ically
ta
ilo
r
ed
to
th
e
u
s
er
d
u
r
in
g
t
h
e
d
i
s
cu
s
s
io
n
.
Fig
u
r
e
4
s
h
o
ws
a
n
e
x
am
p
le
o
f
a
s
ca
tter
p
lo
t
t
h
at
was
m
a
d
e
u
s
in
g
a
s
am
p
le
o
f
co
m
m
en
ts
'
p
o
lar
ity
an
d
s
u
b
jectiv
ity
.
Fro
m
a
c
y
b
er
s
ec
u
r
ity
p
er
s
p
ec
tiv
e,
th
e
u
p
p
er
le
f
t
q
u
ad
r
an
t
o
f
Fig
u
r
e
5
is
o
f
i
m
p
o
r
tan
ce
s
in
ce
it
s
h
o
ws
ce
r
tain
r
em
ar
k
s
th
at
ar
e
h
ig
h
ly
s
u
b
jectiv
e
a
n
d
n
e
g
ativ
ely
p
o
lar
ize
d
.
T
h
ese
co
u
l
d
b
e
r
ef
er
r
ed
t
o
as
d
ata
o
u
tlier
s
th
at
m
er
it f
u
r
t
h
er
ex
a
m
in
atio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
S
en
timen
t a
w
a
r
e
in
tera
ctive
ch
a
tb
o
t A
I
u
s
in
g
mu
lti a
g
en
t p
r
o
ce
s
s
in
g
mo
d
el
(
V
in
o
d
K
u
ma
r
S
h
u
kla
)
205
Fig
u
r
e
3
.
Actu
al
im
p
lem
en
tati
o
n
o
f
C
h
atb
o
t
Fig
u
r
e
4
.
Su
b
jectiv
ity
v
s
p
o
lar
ity
o
f
a
s
am
p
le
o
f
co
m
m
en
ts
Fig
u
r
e
5
(
a)
p
r
esen
ts
a
c
o
m
p
ar
is
o
n
o
f
ev
alu
atio
n
p
a
r
am
eter
s
.
T
h
e
a
cc
u
r
ac
y
o
f
th
e
p
r
o
p
o
s
ed
I
C
h
at
-
AI
ap
p
r
o
ac
h
is
5
.
3
3
%,
4
.
7
3
%,
an
d
1
4
.
3
9
%
h
ig
h
er
th
an
th
e
ex
is
tin
g
R
o
B
E
R
T
a,
T
L
SA,
an
d
MM
T
F
-
DE
S
m
eth
o
d
s
,
r
esp
ec
tiv
ely
.
On
th
e
m
ajo
r
ity
o
f
tech
n
iq
u
es,
th
e
s
u
g
g
ested
m
o
d
el
attain
s
e
x
ce
llen
t
p
r
ec
is
io
n
,
ac
cu
r
ac
y
,
r
ec
all,
an
d
f
1
-
s
co
r
e.
T
h
is
d
em
o
n
s
tr
ates
h
o
w
well
th
e
s
u
g
g
ested
tech
n
iq
u
e
ac
cu
r
ately
class
if
ies
th
e
s
en
tim
en
t
d
etec
tio
n
.
T
h
e
r
esp
o
n
s
e
tim
e
f
lu
ctu
atio
n
with
SA
q
u
er
y
ar
r
i
v
al
r
ate
is
s
h
o
wn
in
Fig
u
r
e
5
(
b
)
.
T
h
e
av
er
ag
e
r
esp
o
n
s
e
tim
e
was
1
5
s
ec
o
n
d
s
f
o
r
3
0
in
q
u
i
r
ies
p
er
s
ec
o
n
d
at
a
6
0
0
-
s
en
ten
c
e
ar
r
iv
al
r
ate.
T
h
e
s
u
g
g
ested
s
y
s
tem
attain
s
s
ig
n
if
ican
t
SA
p
er
f
o
r
m
an
ce
is
s
ca
lab
le
with
s
tr
ea
m
in
g
d
ata,
an
d
f
ac
ilit
ates
o
n
lin
e
r
ea
ctio
n
.
(
a)
(
b
)
Fig
u
r
e
5
.
Per
f
o
r
m
an
c
e
m
etr
ics an
d
r
esp
o
n
s
e
tim
e:
(
a)
m
etr
ic
s
co
m
p
ar
is
o
n
an
d
(
b
)
r
esp
o
n
s
e
tim
e
T
h
e
s
u
g
g
ested
I
C
h
at
-
AI
m
o
d
el
as
s
h
o
wn
in
Fig
u
r
e
6
r
e
s
p
o
n
d
s
m
o
r
e
q
u
ic
k
ly
th
an
th
e
ex
is
tin
g
m
o
d
els.
T
h
e
R
o
B
E
R
T
a
m
eth
o
d
d
em
o
n
s
tr
ates
th
e
h
ig
h
est
q
u
er
y
ex
ec
u
tio
n
tim
e,
m
ain
t
ain
in
g
a
r
elativ
ely
s
tab
le
in
cr
ea
s
e,
wh
ile
T
L
SA
an
d
MM
T
F
-
DE
S
s
h
o
w
m
o
d
e
r
ate
g
r
o
wth
in
e
x
ec
u
tio
n
tim
e
as
th
e
n
u
m
b
er
o
f
q
u
er
ies
r
is
es.
I
n
co
n
tr
ast,
th
e
p
r
o
p
o
s
ed
m
eth
o
d
ex
h
ib
its
th
e
lo
west
q
u
er
y
ex
ec
u
tio
n
tim
e
ac
r
o
s
s
all
q
u
er
y
lev
els,
with
a
s
teep
u
p
war
d
t
r
en
d
,
i
n
d
icatin
g
th
at
it
is
less
ef
f
icien
t
in
h
an
d
lin
g
la
r
g
er
n
u
m
b
er
s
o
f
q
u
er
ies
co
m
p
ar
ed
to
th
e
o
th
er
m
et
h
o
d
s
.
Fig
u
r
e
7
(
a)
r
ep
r
esen
ts
th
e
co
m
p
ar
is
o
n
o
f
c
o
m
p
u
tatio
n
al
co
m
p
lex
ity
.
Am
o
n
g
th
e
an
aly
ze
d
tech
n
iq
u
es,
I
C
h
at
-
AI
e
x
h
ib
its
th
e
h
ig
h
est
ex
ec
u
tio
n
an
d
in
f
e
r
en
ce
tim
e
d
u
e
to
its
in
teg
r
ate
d
DL
an
d
f
ea
tu
r
e
-
r
ich
p
ip
elin
e.
Ho
wev
er
,
th
is
ad
d
ed
co
m
p
lex
ity
s
u
p
p
o
r
ts
en
h
an
ce
d
class
if
icatio
n
ac
cu
r
ac
y
,
m
ak
in
g
it a
s
u
itab
le
tr
ad
e
-
o
f
f
in
h
ig
h
-
s
tak
es
d
ec
is
io
n
-
m
ak
in
g
e
n
v
ir
o
n
m
en
ts
.
T
h
e
s
u
g
g
ested
I
C
h
at
-
AI
m
o
d
el’
s
s
ca
lab
ilit
y
is
co
m
p
ar
ed
to
v
a
r
io
u
s
m
o
d
els
th
at
ar
e
cu
r
r
en
tly
in
u
s
e
in
Fig
u
r
e
7
(
b
)
.
T
h
e
tr
en
d
s
h
o
ws
a
lin
ea
r
in
cr
ea
s
e
in
s
ca
lab
ilit
y
as
th
e
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
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:
2
7
2
2
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DATA AV
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[
1
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