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K
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s
:
Aca
d
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atio
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On
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ly
k
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C
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A
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:
Ph
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T
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T
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N
h
a
T
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an
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Un
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s
ity
02
Ng
u
y
en
Din
h
C
h
ieu
Stre
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,
Nh
a
T
r
an
g
,
Vietn
am
E
m
ail:
th
u
th
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tu
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d
u
.
v
n
1.
I
NT
RO
D
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C
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r
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s
k
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ce
s
.
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s
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tech
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lin
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s
titu
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s
ca
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ett
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m
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f
ac
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in
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esear
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s
tr
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an
d
f
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d
in
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tech
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im
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ely
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o
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h
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th
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ap
p
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eq
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
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J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
On
to
lo
g
y
-
b
a
s
ed
s
ema
n
tic
lin
k
p
r
ed
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n
fo
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en
h
a
n
cin
g
a
ca
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lla
b
o
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…
(
P
h
a
m
Th
i Th
u
Th
u
y
)
1041
Ho
wev
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,
ex
is
tin
g
ap
p
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ac
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e
s
o
f
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lack
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[
1
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,
[
2
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lim
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ig
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[
3
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6
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DB
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Me
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Ou
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s
,
an
d
ac
ad
em
ic
d
is
cip
lin
es.
T
h
e
o
n
t
o
lo
g
y
is
alig
n
ed
with
SKOS
[
1
0
]
an
d
Du
b
lin
C
o
r
e
[
1
1
]
s
tan
d
ar
d
s
to
en
s
u
r
e
in
ter
o
p
er
a
b
ilit
y
an
d
co
n
s
is
ten
cy
ac
r
o
s
s
d
atasets
.
C
o
m
m
u
n
ity
d
etec
tio
n
u
s
in
g
th
e
L
o
u
v
a
in
alg
o
r
ith
m
[
1
2
]
,
SP
AR
QL
-
b
ase
d
s
em
an
tic
f
ea
tu
r
e
ex
tr
ac
tio
n
,
a
n
d
s
u
p
er
v
is
ed
m
ac
h
in
e
lear
n
in
g
m
o
d
els
a
r
e
u
s
ed
to
ev
alu
ate
p
r
ed
ictiv
e
p
e
r
f
o
r
m
an
ce
an
d
d
em
o
n
s
tr
ate
th
e
v
alu
e
o
f
th
is
m
eth
o
d
f
o
r
k
n
o
wled
g
e
-
d
r
i
v
en
d
ec
is
io
n
s
u
p
p
o
r
t
in
ac
ad
em
ic
s
ettin
g
s
.
T
h
e
r
em
ain
d
er
o
f
t
h
is
p
ap
er
is
o
r
g
an
ized
as
f
o
llo
ws.
Sect
io
n
2
r
ev
iews
r
elate
d
wo
r
k
.
Sectio
n
3
d
escr
ib
es
th
e
p
r
o
p
o
s
ed
o
n
to
lo
g
y
-
b
ased
m
eth
o
d
an
d
f
ea
t
u
r
e
co
n
s
tr
u
ctio
n
.
Sectio
n
4
p
r
esen
ts
th
e
ex
p
er
im
e
n
tal
s
etu
p
,
r
esu
lts
,
an
d
co
m
p
ar
ativ
e
an
aly
s
is
.
Sectio
n
5
d
is
cu
s
s
es
th
e
im
p
licatio
n
s
an
d
lim
itatio
n
s
o
f
th
e
f
in
d
in
g
s
.
Sectio
n
6
co
n
cl
u
d
es th
e
p
a
p
er
an
d
o
u
tlin
es d
i
r
ec
tio
n
s
f
o
r
f
u
t
u
r
e
r
esear
ch
.
2.
RE
L
AT
E
D
WO
RK
L
in
k
p
r
ed
ictio
n
in
s
o
cial
an
d
ac
ad
em
ic
n
etwo
r
k
s
h
as
b
ee
n
wid
ely
ex
p
l
o
r
ed
u
s
in
g
s
tr
u
ctu
r
al,
co
n
ten
t
-
b
ased
,
an
d
s
em
an
tic
ap
p
r
o
ac
h
es.
T
r
ad
itio
n
al
m
eth
o
d
s
r
ely
o
n
n
etwo
r
k
to
p
o
lo
g
y
,
s
u
ch
as
co
m
m
o
n
n
ei
g
h
b
o
r
s
o
r
g
r
ap
h
-
b
ased
s
im
ilar
ity
m
ea
s
u
r
es,
o
f
ten
co
m
b
i
n
ed
wit
h
s
u
p
er
v
is
ed
lea
r
n
in
g
m
o
d
els
[
1
]
,
[
2
]
.
Fo
r
in
s
tan
ce
,
Hasan
et
a
l.
[
3
]
ex
t
r
ac
ted
s
tr
u
ctu
r
al
an
d
co
n
ten
t
-
b
ased
f
ea
tu
r
es
f
o
r
s
u
p
er
v
is
ed
lin
k
p
r
ed
ictio
n
in
ac
ad
e
m
ic
n
etwo
r
k
s
,
wh
ile
W
o
h
lf
ar
th
an
d
I
ch
is
e
[
4
]
en
h
an
ce
d
p
r
ed
icti
o
n
u
s
in
g
s
em
an
tic
k
ey
wo
r
d
m
atch
in
g
f
r
o
m
p
ap
er
titl
es.
Similar
ly
,
Sach
an
an
d
I
ch
is
e
[
5
]
in
tr
o
d
u
ce
d
ab
s
tr
ac
t
k
ey
wo
r
d
m
atch
co
u
n
t
(
AKM
C
)
u
s
in
g
J
ac
ca
r
d
s
im
ilar
ity
,
an
d
C
h
u
an
et
a
l.
[
6
]
p
r
o
p
o
s
ed
L
DAc
o
s
in
,
a
t
o
p
ic
m
o
d
elin
g
a
p
p
r
o
ac
h
f
o
r
lin
k
p
r
ed
ictio
n
.
Sev
er
al
s
tu
d
ies
h
av
e
also
ap
p
l
ied
m
ac
h
in
e
lear
n
i
n
g
with
d
o
m
ain
k
n
o
wled
g
e.
Hass
an
[
1
3
]
d
ev
elo
p
ed
a
lin
k
p
r
ed
ictio
n
s
y
s
tem
b
ased
o
n
r
esear
ch
in
ter
ests
an
d
af
f
iliatio
n
s
u
s
in
g
Py
t
h
o
n
,
R
.
C
h
o
an
d
Yu
[
1
4
]
ex
p
lo
r
ed
in
ter
d
is
cip
lin
ar
y
c
o
llab
o
r
atio
n
p
r
ed
ictio
n
u
s
in
g
g
r
ap
h
-
b
ased
m
o
d
els.
Mo
r
e
r
ec
e
n
t
s
tu
d
ies
f
o
cu
s
o
n
s
em
an
tic
lin
k
p
r
e
d
ictio
n
in
o
n
to
lo
g
ies.
C
h
en
et
a
l.
[
1
5
]
,
W
an
et
a
l.
[
1
6
]
ap
p
lied
co
n
tex
tu
al
em
b
ed
d
i
n
g
s
an
d
o
n
to
lo
g
y
co
m
p
leti
o
n
tec
h
n
iq
u
es.
Ma
et
a
l.
[
1
7
]
p
r
o
p
o
s
ed
a
d
ee
p
lear
n
in
g
m
o
d
el
th
at
i
n
teg
r
ates
g
r
ap
h
d
is
tan
ce
an
d
en
tity
s
em
an
tics
to
in
f
er
s
u
b
s
u
m
p
tio
n
lin
k
s
.
On
to
lo
g
y
c
o
n
s
tr
u
ctio
n
h
as
a
ls
o
g
ain
ed
atten
tio
n
f
o
r
d
o
m
ain
-
s
p
ec
if
ic
k
n
o
wled
g
e
m
a
n
ag
em
en
t.
R
esear
ch
er
s
h
av
e
ap
p
lied
o
n
t
o
lo
g
ies
to
ed
u
ca
tio
n
[
1
8
]
,
a
d
m
in
is
tr
atio
n
[
1
9
]
,
f
o
r
estry
[
2
0
]
,
an
d
clim
ate
[
2
1
]
.
Oth
er
s
f
o
cu
s
o
n
o
n
to
lo
g
y
-
e
n
h
an
ce
d
in
f
o
r
m
atio
n
r
etr
iev
a
l
[
2
2
]
–
[
2
4
]
,
e
s
p
ec
ially
i
n
V
ietn
am
ese
co
n
tex
ts
[
2
5
]
–
[
2
7
]
.
I
n
b
ig
d
ata
an
d
m
u
l
tim
ed
ia,
o
n
to
lo
g
y
-
d
r
iv
en
r
e
tr
i
ev
al
h
as
b
ee
n
a
p
p
lied
to
im
ag
e
d
atasets
[
2
8
]
,
[
2
9
]
an
d
W
ik
ip
ed
ia/DB
Ped
ia
-
d
er
iv
ed
o
n
to
l
o
g
ies
[
3
0
]
.
I
n
k
n
o
wled
g
e
m
an
a
g
em
en
t,
s
em
an
tic
tech
n
o
lo
g
ies
ar
e
in
cr
ea
s
in
g
ly
ap
p
lied
f
o
r
s
tr
ateg
ic
r
ea
s
o
n
in
g
an
d
d
ec
is
io
n
s
u
p
p
o
r
t.
Mo
h
a
m
m
ad
et
a
l.
[
3
1
]
p
r
o
p
o
s
ed
a
k
n
o
wled
g
e
g
r
ap
h
-
b
ased
s
y
s
tem
f
o
r
en
ter
p
r
is
e
k
n
o
wled
g
e
s
er
v
ices,
r
ein
f
o
r
cin
g
th
e
u
tili
ty
o
f
s
tr
u
ctu
r
ed
s
e
m
an
tic
m
o
d
els
in
o
r
g
a
n
izatio
n
al
lear
n
in
g
,
a
n
i
d
ea
ce
n
tr
al
to
o
u
r
wo
r
k
.
I
n
s
u
m
m
a
r
y
,
p
r
io
r
s
tu
d
ies
h
a
v
e
ef
f
ec
tiv
ely
ex
p
lo
ited
s
tr
u
ct
u
r
al
f
ea
tu
r
es
[
1
]
,
[
2
]
,
c
o
n
ten
t
an
d
to
p
ic
s
im
ilar
ity
[
3
]
-
[
6
]
,
a
n
d
o
n
to
lo
g
y
-
b
ased
r
e
p
r
esen
tatio
n
s
f
o
r
r
et
r
iev
al
an
d
co
m
p
letio
n
task
s
[
1
5
]
-
[
1
7
]
,
[
2
2
]
-
[
3
0
]
.
Ho
wev
er
,
th
ey
g
e
n
er
ally
d
o
n
o
t
in
teg
r
ate
h
eter
o
g
en
eo
u
s
s
ch
o
lar
ly
m
etad
ata
(
e.
g
.
,
r
e
ad
er
s
h
ip
,
d
is
cip
lin
e
tax
o
n
o
m
ies
,
p
u
b
licatio
n
ty
p
e
s
)
in
to
a
s
in
g
le
SKOS
-
an
d
Du
b
lin
C
o
r
e
–
alig
n
e
d
o
n
to
lo
g
y
,
a
n
d
th
ey
r
ar
ely
co
m
b
in
e
s
u
c
h
s
em
an
tic
en
r
i
ch
m
en
t
with
tem
p
o
r
al
co
lla
b
o
r
atio
n
h
is
to
r
y
f
o
r
lin
k
p
r
ed
ictio
n
.
Ou
r
wo
r
k
ad
d
r
ess
es
th
is
g
ap
b
y
c
o
n
s
tr
u
ctin
g
a
u
n
if
ied
ac
ad
em
ic
o
n
to
lo
g
y
o
v
er
AM
in
er
,
DB
L
P,
an
d
Me
n
d
ele
y
an
d
b
y
em
p
ir
ically
ev
alu
atin
g
th
e
ad
d
ed
v
al
u
e
o
f
o
n
to
lo
g
y
-
b
ased
s
em
an
tic
an
d
tem
p
o
r
al
f
ea
tu
r
es
ag
ain
s
t
s
tr
u
ctu
r
al
b
aselin
es.
3.
M
E
T
H
O
D
3
.
1
.
G
ra
ph
co
ns
t
ruct
io
n a
nd
o
nto
lo
g
y
inte
g
ra
t
i
o
n
T
o
b
u
ild
a
co
m
p
r
eh
e
n
s
iv
e
ac
ad
em
ic
k
n
o
wled
g
e
g
r
ap
h
,
we
in
teg
r
ate
th
r
ee
m
ajo
r
d
atasets
:
AM
in
er
,
DB
L
P,
an
d
Me
n
d
eley
.
E
ac
h
o
f
f
er
s
co
m
p
lem
en
tar
y
m
eta
d
a
ta
-
AM
in
er
p
r
o
v
id
es
co
-
au
th
o
r
s
h
ip
an
d
citatio
n
d
ata;
DB
L
P
co
n
tr
ib
u
tes
s
tr
u
ctu
r
ed
p
u
b
licatio
n
an
d
v
en
u
e
in
f
o
r
m
atio
n
;
an
d
Me
n
d
ele
y
ad
d
s
r
ea
d
er
s
h
i
p
,
d
o
cu
m
e
n
t ty
p
es,
an
d
d
is
cip
lin
e
tag
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
3
,
Ma
r
ch
20
2
6
:
1
0
4
0
-
1
0
4
8
1042
T
h
ese
d
atas
ets
ar
e
u
n
if
ie
d
t
h
r
o
u
g
h
a
s
h
a
r
e
d
o
n
t
o
l
o
g
y
d
ev
el
o
p
e
d
i
n
P
r
o
té
g
é
u
s
i
n
g
t
h
e
C
el
lf
i
e
p
l
u
g
in
[
3
2
]
.
T
h
e
o
n
t
o
l
o
g
y
i
n
cl
u
d
e
s
c
o
r
e
class
es
s
u
c
h
as
A
u
th
o
r
,
Pu
b
l
ica
ti
o
n
,
Af
f
i
lia
ti
o
n
,
R
es
ea
r
c
h
I
n
te
r
est
,
Do
c
u
m
e
n
t
T
y
p
e,
V
e
n
u
e,
a
n
d
Aca
d
e
m
i
cDisc
ip
li
n
e
,
as
v
is
u
a
lize
d
i
n
Fi
g
u
r
e
1
.
S
em
a
n
ti
c
r
elat
io
n
s
h
i
p
s
a
m
o
n
g
th
es
e
e
n
tit
ies
a
r
e
m
o
d
el
e
d
u
s
in
g
o
b
je
ct
p
r
o
p
e
r
ti
es
l
i
k
e
h
asAf
f
il
iat
io
n
,
h
asDis
c
ip
li
n
e
,
an
d
h
asP
u
b
l
ic
ati
o
n
(
Fi
g
u
r
e
2
)
.
T
o
en
s
u
r
e
in
te
r
o
p
er
a
b
ilit
y
,
w
e
alig
n
k
ey
co
m
p
o
n
en
ts
with
estab
lis
h
ed
s
tan
d
ar
d
s
:
SKOS
is
u
s
ed
f
o
r
co
n
tr
o
lled
c
o
n
ce
p
ts
(
e.
g
.
,
Do
cu
m
en
tTy
p
e
,
Aca
d
em
icDiscip
lin
e
)
,
an
d
Du
b
lin
C
o
r
e
f
o
r
m
etad
ata
an
n
o
tatio
n
s
(
e.
g
.
,
d
cter
m
s
:
ty
p
e,
d
cter
m
s
:
p
u
b
lis
h
er
)
.
T
h
is
s
em
an
tic
alig
n
m
en
t
en
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r
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o
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ata
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tic
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ased
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ata
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r
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u
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u
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ics
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ied
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ati
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tic
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ai
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u
r
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1
.
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lass
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aliza
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r
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2
.
Ob
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r
o
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.
2
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f
iliatio
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ich
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eg
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ased
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lect
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ip
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atter
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ased
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r
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u
r
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4
s
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ier
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e
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ates
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u
r
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3
.
Data
im
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r
t r
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lt o
f
th
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Fig
u
r
e
4
.
Data
p
r
o
p
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r
ty
v
is
u
al
izatio
n
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
s
ec
tio
n
p
r
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ts
th
e
ex
p
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im
en
tal
s
etu
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m
etr
ics,
an
d
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f
o
r
m
a
n
ce
r
es
u
lts
o
f
o
u
r
o
n
to
lo
g
y
-
b
ased
lin
k
p
r
ed
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n
f
r
am
ewo
r
k
.
T
h
e
ev
alu
ati
o
n
is
d
esig
n
ed
to
ass
es
s
th
e
ef
f
ec
tiv
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o
g
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eo
u
s
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ch
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lar
ly
d
atasets
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d
s
em
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ti
c
f
ea
tu
r
es
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en
h
a
n
cin
g
p
r
e
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ictiv
e
ac
cu
r
ac
y
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d
k
n
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is
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v
er
y
.
4
.
1
.
F
e
a
t
ure
enco
din
g
a
nd
lea
rning
s
et
up
E
ac
h
au
th
o
r
p
air
was
r
e
p
r
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n
ted
b
y
a
f
ea
tu
r
e
v
ec
to
r
th
at
co
m
b
in
es
b
o
th
s
tr
u
ctu
r
al
an
d
s
em
an
tic
d
im
en
s
io
n
s
to
ca
p
tu
r
e
th
e
co
m
p
lex
ity
o
f
ac
ad
em
ic
co
llab
o
r
atio
n
.
T
h
e
tem
p
o
r
al
f
ea
tu
r
es
in
clu
d
e
h
asS
tatu
s
3
,
h
asS
tatu
s
2
,
an
d
h
asS
tatu
s
1
,
wh
ich
r
ef
lect
th
e
n
u
m
b
e
r
o
f
co
-
au
th
o
r
s
h
i
p
s
o
v
er
th
e
p
ast
th
r
ee
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ea
r
s
.
T
h
e
s
em
an
tic
f
ea
tu
r
es
co
n
s
is
t
o
f
h
asC
o
m
m
o
n
Af
f
iliatio
n
,
h
asC
o
m
m
o
n
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n
ter
est,
h
as
Dis
cip
lin
eSim
ilar
ity
,
h
asR
ea
d
er
Ov
er
lap
,
a
n
d
h
asP
u
b
licatio
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T
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p
eSim
ilar
ity
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all
o
f
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ich
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r
e
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er
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v
ed
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r
o
m
th
e
e
n
r
ich
ed
o
n
t
o
lo
g
y
t
o
r
ep
r
esen
t in
s
titu
tio
n
al,
to
p
ical,
d
is
cip
lin
ar
y
,
r
ea
d
er
s
h
ip
,
a
n
d
p
u
b
licatio
n
-
ty
p
e
s
im
ilar
ities
b
etwe
en
au
th
o
r
s
.
T
h
ese
f
ea
tu
r
es
wer
e
a
u
to
m
a
tically
ex
tr
ac
ted
f
r
o
m
t
h
e
o
n
to
lo
g
y
u
s
in
g
SP
AR
QL
q
u
er
ies
an
d
co
n
v
er
ted
in
to
n
u
m
er
ical
f
ea
tu
r
e
v
ec
to
r
s
f
o
r
in
p
u
t
t
o
m
ac
h
i
n
e
lear
n
in
g
m
o
d
els.
Fig
u
r
e
5
p
r
o
v
id
es
a
n
ex
am
p
le
o
f
a
SP
AR
QL
q
u
er
y
u
s
ed
t
o
co
m
p
u
te
co
m
m
o
n
af
f
iliatio
n
s
co
r
es.
Mo
d
els
we
r
e
tr
ain
e
d
u
s
in
g
s
cik
it
-
lear
n
f
o
r
class
ical
c
lass
if
ier
s
,
an
d
g
r
ap
h
n
eu
r
al
n
etwo
r
k
v
ar
ia
n
ts
wer
e
im
p
lem
en
ted
u
s
in
g
a
s
tan
d
ar
d
d
ee
p
lear
n
in
g
lib
r
ar
y
f
o
r
g
r
ap
h
-
b
ased
r
ea
s
o
n
in
g
.
T
h
e
f
in
al
d
ataset
in
clu
d
es
3
3
1
2
au
th
o
r
s
an
d
1
4
2
6
8
au
th
o
r
p
air
s
,
with
7
1
3
4
p
o
s
itiv
e
(
ex
is
tin
g
co
llab
o
r
atio
n
)
an
d
7
1
3
4
n
eg
ativ
e
(
n
o
n
-
co
l
lab
o
r
atio
n
)
i
n
s
tan
ce
s
.
W
e
r
an
d
o
m
ly
s
p
lit
th
e
d
ata
in
to
7
0
% tr
ain
in
g
,
1
5
% v
alid
a
tio
n
,
an
d
1
5
% test sets
,
s
tr
atif
i
ed
b
y
class
lab
el
to
p
r
eser
v
e
t
h
e
p
o
s
itiv
e/n
eg
ativ
e
r
atio
.
Fo
r
t
r
ad
itio
n
al
m
ac
h
i
n
e
lear
n
in
g
m
o
d
els,
we
u
s
ed
s
cik
it
-
lear
n
im
p
lem
en
tati
o
n
s
an
d
tu
n
e
d
k
e
y
h
y
p
er
p
ar
am
eter
s
(
s
u
ch
as
r
eg
u
lar
izatio
n
s
tr
en
g
th
f
o
r
lo
g
is
tic
r
eg
r
ess
io
n
an
d
n
u
m
b
er
o
f
tr
ee
s
an
d
m
ax
im
u
m
d
ep
th
f
o
r
r
an
d
o
m
f
o
r
est
)
o
n
t
h
e
v
alid
atio
n
s
et.
Fo
r
th
e
GNN,
we
tr
ain
ed
a
two
-
lay
er
ar
c
h
itectu
r
e
with
n
o
n
-
lin
ea
r
ac
tiv
atio
n
an
d
ea
r
ly
s
to
p
p
in
g
b
ased
o
n
v
alid
atio
n
l
o
s
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
3
,
Ma
r
ch
20
2
6
:
1
0
4
0
-
1
0
4
8
1044
Fig
u
r
e
5
.
SP
AR
QL
to
ex
tr
ac
t
co
m
m
o
n
af
f
iliatio
n
Fig
u
r
e
5
illu
s
tr
ates
th
e
ex
ec
u
t
io
n
o
f
a
SP
AR
QL
q
u
er
y
d
esig
n
ed
to
c
o
m
p
u
te
th
e
n
u
m
b
er
o
f
co
m
m
o
n
in
s
titu
tio
n
al
af
f
iliatio
n
s
b
etwe
en
p
air
s
o
f
au
th
o
r
s
with
in
th
e
in
teg
r
ated
o
n
to
lo
g
y
.
T
h
e
q
u
er
y
s
elec
ts
all
d
is
tin
ct
af
f
iliatio
n
s
(
?a
f
f
)
th
at
a
r
e
s
h
ar
ed
b
y
a
n
y
two
au
t
h
o
r
s
(
?a
u
t
h
o
r
1
an
d
?a
u
th
o
r
2
)
a
n
d
ap
p
lies
a
f
ilter
to
en
s
u
r
e
th
at
o
n
ly
n
o
n
-
id
en
tical
au
th
o
r
p
air
s
ar
e
co
n
s
id
er
ed
.
T
h
e
q
u
er
y
was
ex
ec
u
ted
o
n
a
SP
A
R
QL
en
d
p
o
i
n
t
s
u
p
p
o
r
tin
g
th
e
o
n
to
lo
g
y
at
h
ttp
:
//w
w
w
.
ex
a
mp
le.
co
m/o
n
to
l
o
g
ies/
myo
n
to
lo
g
y#
.
As
s
h
o
wn
in
th
e
r
esu
lt
p
an
el,
th
e
s
y
s
tem
id
en
tifie
d
3
,
4
7
6
s
h
ar
ed
af
f
iliatio
n
in
s
tan
ce
s
,
in
d
icatin
g
a
h
ig
h
lev
el
o
f
in
s
titu
tio
n
al
o
v
er
lap
am
o
n
g
th
e
au
th
o
r
s
in
th
e
d
ataset.
T
h
is
f
ea
tu
r
e,
la
b
eled
co
m
m
o
n
Af
f
iliatio
n
C
o
u
n
t
,
is
u
s
ed
as
a
s
em
an
tic
s
im
i
lar
ity
m
etr
ic
in
th
e
lin
k
p
r
ed
ictio
n
m
o
d
el
to
en
h
an
ce
its
ab
ilit
y
to
f
o
r
ec
ast f
u
tu
r
e
ac
ad
em
ic
co
llab
o
r
atio
n
s
.
I
n
p
r
ac
tice,
th
is
q
u
er
y
is
p
ar
t
o
f
a
f
am
ily
o
f
p
ar
am
ete
r
ized
SP
AR
QL
tem
p
lates
th
at
ar
e
iter
ativ
ely
ex
ec
u
ted
o
v
er
all
ca
n
d
id
ate
a
u
th
o
r
p
ai
r
s
to
co
m
p
u
te
s
em
a
n
tic
f
ea
tu
r
es
s
u
ch
as
co
m
m
o
n
af
f
iliatio
n
,
s
h
ar
ed
in
ter
ests
,
d
is
cip
lin
e
s
im
ilar
ity
,
an
d
r
ea
d
er
o
v
er
la
p
.
T
h
is
d
esi
g
n
allo
ws
t
h
e
f
ea
t
u
r
e
ex
tr
ac
ti
o
n
p
r
o
ce
s
s
to
s
ca
le
to
lar
g
e
n
u
m
b
er
s
o
f
p
air
s
wh
il
e
k
ee
p
in
g
th
e
SP
AR
QL
lo
g
ic
m
o
d
u
lar
a
n
d
r
eu
s
ab
le.
4
.
2
.
Resul
t
s
a
nd
co
m
pa
ra
t
i
v
e
a
na
ly
s
is
E
x
p
er
im
en
ts
d
e
m
o
n
s
tr
ate
th
a
t
in
co
r
p
o
r
atin
g
o
n
to
l
o
g
y
-
b
ased
f
ea
tu
r
es
s
ig
n
if
ica
n
tly
im
p
r
o
v
es
lin
k
p
r
ed
ictio
n
p
er
f
o
r
m
a
n
ce
.
T
h
e
ex
p
er
im
en
tal
r
esu
lts
ar
e
p
r
esen
ted
in
F
ig
u
r
es
6
-
9
,
wh
ich
s
u
m
m
ar
ize
class
if
icatio
n
ac
cu
r
ac
y
,
F1
-
s
c
o
r
e,
AUC
,
an
d
r
an
k
in
g
m
etr
ics
ac
r
o
s
s
th
e
ev
alu
ated
m
o
d
e
ls
.
T
o
g
eth
er
,
th
ese
f
ig
u
r
es h
ig
h
lig
h
t th
e
im
p
ac
t o
f
b
o
th
s
em
an
tic
an
d
tem
p
o
r
al
f
ea
tu
r
es o
n
co
llab
o
r
atio
n
f
o
r
ec
asti
n
g
.
Fig
u
r
e
6
s
h
o
ws
m
o
d
el
p
er
f
o
r
m
an
ce
with
a
4
-
f
ea
tu
r
e
s
etu
p
,
in
clu
d
in
g
cu
r
r
e
n
t
co
-
a
u
th
o
r
s
h
ip
an
d
b
asic
s
em
an
tic
attr
ib
u
tes
lik
e
a
f
f
iliatio
n
an
d
r
esear
c
h
in
ter
est.
L
o
g
is
tic
r
eg
r
ess
io
n
an
d
r
an
d
o
m
f
o
r
est
y
ield
s
tr
o
n
g
r
esu
lts
(
8
4
.
3
% a
n
d
8
6
.
2
% a
cc
u
r
ac
y
)
,
co
n
f
i
r
m
in
g
t
h
e
ef
f
ec
tiv
en
ess
o
f
ev
en
m
i
n
im
al
s
em
an
t
ic
f
ea
tu
r
es.
Fig
u
r
e
6
.
Per
f
o
r
m
an
c
e
co
m
p
ar
is
o
n
o
f
m
o
d
els u
s
in
g
th
e
4
-
f
ea
tu
r
e
co
n
f
ig
u
r
atio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
On
to
lo
g
y
-
b
a
s
ed
s
ema
n
tic
lin
k
p
r
ed
ictio
n
fo
r
en
h
a
n
cin
g
a
ca
d
emic
co
lla
b
o
r
a
tio
n
…
(
P
h
a
m
Th
i Th
u
Th
u
y
)
1045
Fig
u
r
e
7
.
Per
f
o
r
m
an
c
e
co
m
p
ar
is
o
n
o
f
m
o
d
els u
s
in
g
th
e
5
-
f
ea
tu
r
e
co
n
f
ig
u
r
atio
n
Fig
u
r
e
7
c
o
m
p
a
r
es
m
o
d
els
u
s
in
g
a
5
-
f
ea
tu
r
e
co
n
f
i
g
u
r
ati
o
n
th
at
i
n
cl
u
d
es
t
h
r
e
e
y
e
a
r
s
o
f
h
is
to
r
i
ca
l
co
l
la
b
o
r
ati
o
n
.
Ad
d
i
n
g
t
em
p
o
r
al
f
ea
tu
r
es
b
o
o
s
ts
a
ll
m
et
r
i
cs
,
wit
h
G
NN
a
n
d
r
a
n
d
o
m
f
o
r
est
o
u
tp
er
f
o
r
m
i
n
g
b
as
eli
n
es
-
GN
N
ac
h
i
e
v
es
9
1
.
2
%
a
cc
u
r
ac
y
an
d
8
9
.
8
%
F
1
-
s
c
o
r
e.
T
h
e
i
m
p
r
o
v
e
m
e
n
t
o
v
e
r
t
r
ad
i
ti
o
n
al
m
o
d
els
f
o
r
co
-
a
u
t
h
o
r
s
h
i
p
l
i
n
k
p
r
e
d
i
cti
o
n
,
s
u
c
h
as
th
e
s
u
p
er
v
is
e
d
s
t
r
u
ct
u
r
al
a
p
p
r
o
a
ch
o
f
Al
Hasa
n
et
a
l.
[
3
]
,
t
h
e
s
em
an
tic
en
h
a
n
ce
m
e
n
ts
o
f
S
ac
h
a
n
a
n
d
I
ch
is
e
[
1
1
]
,
a
n
d
t
h
e
h
y
b
r
i
d
c
o
n
ten
t
-
b
ase
d
m
et
h
o
d
o
f
C
h
u
a
n
e
t
a
l
.
[
6
]
,
h
i
g
h
li
g
h
ts
th
e
ad
v
an
ta
g
e
o
f
c
o
m
b
i
n
i
n
g
t
e
m
p
o
r
al
an
d
o
n
to
lo
g
y
-
b
ase
d
f
e
atu
r
es.
T
h
e
o
v
e
r
a
ll
p
er
f
o
r
m
a
n
ce
is
als
o
c
o
n
s
is
t
en
t
wit
h
r
e
ce
n
t
s
e
m
a
n
t
ic
e
m
b
e
d
d
i
n
g
-
b
ase
d
a
p
p
r
o
ac
h
es
s
u
c
h
as
C
h
e
n
et
a
l.
[
1
5
]
,
i
n
d
i
ca
t
in
g
t
h
at
o
u
r
f
r
a
m
ew
o
r
k
is
co
m
p
eti
ti
v
e
wi
th
in
t
h
e
c
u
r
r
e
n
t
s
tate
o
f
t
h
e
a
r
t
i
n
s
em
a
n
ti
c
l
in
k
p
r
e
d
i
cti
o
n
f
o
r
ac
a
d
em
i
c
n
etw
o
r
k
s
.
Fig
u
r
e
8
p
r
esen
ts
AUC
s
co
r
es,
clea
r
ly
f
av
o
r
in
g
o
n
t
o
lo
g
y
-
e
n
h
an
ce
d
m
o
d
els
(
AUC
0
.
9
2
-
0
.
9
6
)
o
v
e
r
s
tr
u
ctu
r
e
-
o
n
l
y
b
aselin
es
(
<0
.
8
6
)
.
T
h
is
u
n
d
er
s
co
r
es
th
e
b
en
e
f
it
o
f
in
co
r
p
o
r
atin
g
s
em
an
tic
f
ea
tu
r
e
s
f
o
r
b
etter
class
s
ep
ar
ab
ilit
y
an
d
p
r
ed
icti
o
n
r
eliab
ilit
y
.
Fig
u
r
e
8
.
AUC d
is
tr
ib
u
tio
n
b
y
o
n
to
lo
g
y
u
s
ag
e
Fig
u
r
e
9
.
MRR
an
d
Hits
@
K
v
alu
es a
cr
o
s
s
m
o
d
els
Fig
u
r
e
9
d
is
p
lay
s
a
h
ex
b
i
n
p
l
o
t
s
h
o
win
g
th
e
r
elatio
n
s
h
ip
b
e
twee
n
m
ea
n
r
ec
ip
r
o
ca
l
r
an
k
(
MRR
)
an
d
Hits
@
K
f
o
r
all
ev
alu
ated
m
o
d
els.
Dar
k
er
a
r
ea
s
in
d
icate
h
i
g
h
er
p
r
ed
ictio
n
d
en
s
ity
,
r
ev
ea
lin
g
a
clea
r
u
p
war
d
tr
en
d
-
m
o
d
els
with
h
ig
h
er
Hits
@
K
also
ten
d
to
ac
h
iev
e
h
i
g
h
er
MRR
,
r
ef
lectin
g
s
tr
o
n
g
r
an
k
i
n
g
p
r
ec
is
io
n
.
On
to
lo
g
y
-
b
ased
m
o
d
els,
esp
ec
ially
th
o
s
e
u
s
in
g
s
em
an
tic
a
n
d
tem
p
o
r
al
f
ea
tu
r
es,
clu
s
ter
in
th
e
u
p
p
er
-
r
ig
h
t
r
eg
io
n
,
h
ig
h
lig
h
tin
g
th
eir
ef
f
ec
tiv
en
ess
in
id
en
tify
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o
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s
t
lik
ely
b
u
t
h
ig
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ly
r
elev
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t c
o
llab
o
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at
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s
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x
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ts
co
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r
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t
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is
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(
h
as
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s
3
to
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at
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1
)
,
s
ig
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if
i
ca
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t
ly
e
n
h
an
ce
p
r
e
d
i
cti
o
n
ac
c
u
r
ac
y
.
R
a
n
d
o
m
f
o
r
est
a
n
d
lo
g
is
tic
r
e
g
r
ess
io
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c
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s
is
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en
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t
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e
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f
o
r
m
s
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GNNs
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w
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g
p
r
o
m
is
e
f
o
r
f
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r
e
w
o
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k
.
Acr
o
s
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all
m
etr
ics,
o
n
to
lo
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y
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en
h
an
ce
d
m
o
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tp
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f
o
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tr
ad
itio
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ap
p
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R
an
d
o
m
f
o
r
est
an
d
lo
g
is
tic
r
eg
r
ess
io
n
,
wh
en
en
r
ich
ed
with
s
em
an
tic
an
d
tem
p
o
r
al
f
ea
tu
r
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ap
p
r
o
ac
h
9
0
%
ac
cu
r
ac
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an
d
y
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d
s
tr
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MRR
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d
AUC
s
co
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es.
I
n
co
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t
r
ast,
m
o
d
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b
ased
s
o
lely
o
n
s
tr
u
ctu
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r
co
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ten
t
s
im
ilar
ity
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
5
0
2
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4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
41
,
No
.
3
,
Ma
r
ch
20
2
6
:
1
0
4
0
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1
0
4
8
1046
p
er
f
o
r
m
n
o
tab
ly
wo
r
s
e.
T
h
e
s
e
f
in
d
in
g
s
u
n
d
er
s
co
r
e
th
e
v
alu
e
o
f
co
m
b
in
in
g
o
n
to
lo
g
i
ca
l
r
ea
s
o
n
in
g
with
co
llab
o
r
atio
n
h
is
to
r
y
to
im
p
r
o
v
e
lin
k
p
r
ed
ictio
n
,
p
ar
ticu
lar
ly
in
s
p
ar
s
e
ac
ad
em
ic
n
etwo
r
k
s
.
C
o
m
p
ar
ed
with
o
n
to
lo
g
y
-
b
as
ed
an
d
s
em
an
tic
lin
k
p
r
ed
ic
tio
n
m
eth
o
d
s
in
th
e
liter
atu
r
e
[
3
]
-
[
6
]
,
[
1
5
]
,
[
1
7
]
,
o
u
r
b
est
m
o
d
els
ac
h
iev
e
co
m
p
etitiv
e
o
r
h
i
g
h
er
a
cc
u
r
ac
y
an
d
r
an
k
in
g
p
er
f
o
r
m
a
n
ce
wh
ile
o
p
er
atin
g
o
n
a
r
ich
er
f
ea
tu
r
e
s
p
a
ce
th
at
jo
in
tly
en
co
d
es
s
tr
u
ctu
r
e
,
tim
e,
an
d
SKOS
-
alig
n
ed
s
em
an
ti
cs.
Alth
o
u
g
h
ex
ac
t
ex
p
er
im
en
tal
s
ettin
g
s
d
if
f
er
a
cr
o
s
s
s
tu
d
ies,
th
e
co
n
s
is
ten
t
g
ain
s
o
f
o
n
to
lo
g
y
-
en
h
a
n
ce
d
f
ea
tu
r
es
o
v
er
o
u
r
o
w
n
s
tr
u
ctu
r
al
b
aselin
es
s
u
g
g
est
th
at
s
em
an
tic
m
o
d
elin
g
ad
d
s
co
m
p
le
m
en
tar
y
in
f
o
r
m
atio
n
b
ey
o
n
d
wh
at
is
ca
p
tu
r
ed
b
y
n
etwo
r
k
m
etr
ics a
lo
n
e.
4
.
3
.
Dis
cus
s
io
n
T
h
e
e
x
p
e
r
i
m
e
n
t
al
r
es
u
lts
s
h
o
w
th
at
i
n
t
eg
r
a
ti
n
g
s
e
m
a
n
ti
c
a
n
d
tem
p
o
r
al
f
e
at
u
r
es
s
i
g
n
i
f
ic
a
n
tl
y
im
p
r
o
v
es
th
e
p
r
e
d
i
cti
o
n
o
f
ac
a
d
em
i
c
c
o
lla
b
o
r
ati
o
n
s
c
o
m
p
a
r
ed
to
s
tr
u
ctu
r
e
-
o
n
l
y
b
ase
li
n
es
.
On
t
o
l
o
g
y
-
e
n
h
a
n
ce
d
m
o
d
els
d
e
m
o
n
s
tr
ate
h
i
g
h
er
a
cc
u
r
ac
y
,
F1
-
s
c
o
r
e
,
AUC,
a
n
d
r
a
n
k
i
n
g
m
e
tr
i
cs,
c
o
n
f
ir
m
i
n
g
th
at
s
em
a
n
t
ic
e
n
r
ic
h
m
e
n
t
p
r
o
v
i
d
es
m
ea
n
i
n
g
f
u
l
c
o
n
te
x
t
n
o
t
c
a
p
t
u
r
ed
b
y
tr
ad
iti
o
n
al
t
o
p
o
l
o
g
ica
l
m
ea
s
u
r
es
.
T
h
ese
f
i
n
d
i
n
g
s
a
r
e
c
o
n
s
is
t
e
n
t
wit
h
ea
r
l
ie
r
w
o
r
k
t
h
a
t
i
n
c
o
r
p
o
r
at
es
c
o
n
te
n
t
an
d
s
em
an
tic
in
f
o
r
m
a
ti
o
n
in
to
li
n
k
p
r
e
d
i
cti
o
n
[
3
]
-
[
6
]
,
[
1
5
]
,
b
u
t
o
u
r
s
tu
d
y
f
u
r
t
h
er
c
o
m
b
in
es
h
is
to
r
y
a
n
d
SK
OS
-
ali
g
n
e
d
d
is
ci
p
l
in
ar
y
k
n
o
wle
d
g
e
d
e
r
i
v
e
d
f
r
o
m
a
u
n
i
f
ie
d
o
n
t
o
l
o
g
y
.
Fro
m
an
ap
p
licatio
n
p
er
s
p
ec
ti
v
e,
th
e
f
r
am
ewo
r
k
is
r
elev
an
t
f
o
r
in
s
titu
tio
n
s
th
at
aim
to
b
u
ild
d
ata
-
d
r
iv
en
r
esear
ch
er
r
ec
o
m
m
e
n
d
atio
n
s
y
s
tem
s
an
d
to
m
o
n
ito
r
th
e
ev
o
lu
tio
n
o
f
r
esear
ch
co
m
m
u
n
ities
.
Sem
an
tic
f
ea
tu
r
es
s
u
ch
as
af
f
iliatio
n
,
d
is
cip
lin
e
s
im
ilar
ity
,
an
d
r
ea
d
er
s
h
ip
o
v
er
la
p
h
elp
id
en
tif
y
p
r
o
m
is
in
g
co
llab
o
r
atio
n
o
p
p
o
r
tu
n
ities
th
at
a
r
e
n
o
t
o
b
v
io
u
s
f
r
o
m
s
tr
u
ctu
r
e
alo
n
e,
t
h
er
eb
y
s
u
p
p
o
r
tin
g
ex
p
er
t
r
ec
o
m
m
en
d
atio
n
,
tea
m
f
o
r
m
atio
n
,
an
d
th
e
d
etec
tio
n
o
f
em
er
g
in
g
r
esear
ch
cl
u
s
ter
s
.
T
h
ese
ca
p
ab
ilit
ies
alig
n
with
th
e
b
r
o
ad
er
r
o
le
o
f
s
em
an
tic
tech
n
o
l
o
g
ies in
k
n
o
wled
g
e
m
an
ag
e
m
en
t a
n
d
d
ec
is
io
n
s
u
p
p
o
r
t [
3
1
]
.
T
h
is
wo
r
k
h
as
s
ev
er
al
lim
itat
io
n
s
th
at
s
u
g
g
est
d
ir
ec
tio
n
s
f
o
r
f
u
tu
r
e
r
esear
ch
.
First,
th
e
o
n
to
lo
g
y
is
n
o
t
y
et
in
teg
r
ated
with
ex
p
licit
tem
p
o
r
al
o
n
to
lo
g
ies
s
u
ch
as
OW
L
-
T
im
e,
wh
ich
wo
u
ld
e
n
ab
le
m
o
r
e
ex
p
r
ess
iv
e
r
ea
s
o
n
in
g
a
b
o
u
t
th
e
ev
o
lu
tio
n
o
f
c
o
llab
o
r
ati
o
n
s
.
Seco
n
d
,
we
d
id
n
o
t
e
x
h
au
s
tiv
ely
ex
p
lo
r
e
alter
n
ativ
e
g
r
ap
h
n
e
u
r
al
ar
ch
i
tectu
r
es
o
r
lar
g
e
la
n
g
u
a
g
e
m
o
d
el
-
b
ased
r
e
p
r
esen
tatio
n
s
,
w
h
ich
co
u
l
d
f
u
r
th
er
im
p
r
o
v
e
p
er
f
o
r
m
an
ce
.
T
h
ir
d
,
r
ea
l
-
wo
r
ld
ev
alu
atio
n
in
in
s
titu
tio
n
al
s
ettin
g
s
(
e.
g
.
,
th
r
o
u
g
h
u
s
er
s
tu
d
ies
o
r
d
ep
lo
y
m
e
n
t in
r
esear
ch
s
u
p
p
o
r
t to
o
ls
)
r
em
ain
s
an
im
p
o
r
ta
n
t
o
p
en
s
tep
.
I
n
s
u
m
m
ar
y
,
th
e
r
esu
lts
in
d
icate
th
at
co
m
b
in
in
g
m
u
lti
-
s
o
u
r
ce
s
em
an
tic
in
teg
r
atio
n
with
m
ac
h
in
e
lear
n
in
g
p
r
o
v
id
es
an
ef
f
ec
tiv
e
an
d
e
x
p
lain
ab
le
f
r
am
ewo
r
k
f
o
r
ac
ad
em
ic
co
llab
o
r
atio
n
p
r
e
d
ictio
n
,
wh
ile
also
o
p
en
in
g
o
p
p
o
r
tu
n
ities
f
o
r
r
ich
er
r
ea
s
o
n
in
g
an
d
v
alid
atio
n
in
f
u
tu
r
e
wo
r
k
.
5.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
p
r
esen
ts
an
o
n
to
lo
g
y
-
b
ased
s
em
an
tic
lin
k
p
r
ed
ictio
n
f
r
am
ew
o
r
k
t
h
at
ad
d
r
ess
es
th
e
g
r
o
win
g
n
ee
d
f
o
r
in
tellig
en
t
co
llab
o
r
atio
n
f
o
r
ec
asti
n
g
in
ac
ad
em
ic
en
v
ir
o
n
m
en
ts
.
B
y
in
teg
r
atin
g
co
-
au
th
o
r
s
h
ip
d
ata
f
r
o
m
AM
in
er
,
DB
L
P,
an
d
Me
n
d
eley
in
to
a
u
n
if
ied
o
n
to
lo
g
y
,
a
n
d
alig
n
in
g
it
with
SKOS
an
d
Du
b
lin
C
o
r
e
s
tan
d
ar
d
s
,
we
co
n
s
tr
u
cted
a
r
ich
s
em
an
tic
r
ep
r
es
en
tatio
n
o
f
s
ch
o
lar
ly
r
elatio
n
s
h
ip
s
an
d
r
esear
ch
co
n
tex
ts
.
T
h
e
f
r
am
ewo
r
k
c
o
m
b
in
es
s
tr
u
ctu
r
al,
tem
p
o
r
a
l,
an
d
s
em
an
tic
f
ea
tu
r
es
to
in
f
er
p
o
ten
tial
co
llab
o
r
atio
n
s
,
lev
e
r
ag
in
g
b
o
t
h
r
u
le
-
b
ased
r
ea
s
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Un
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Evaluation Warning : The document was created with Spire.PDF for Python.
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1047
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ttp
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ttp
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lp
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RE
F
E
R
E
NC
E
S
[
1
]
F
.
G
a
o
,
K
.
M
u
si
a
l
,
C
.
C
o
o
p
e
r
,
a
n
d
S
.
Ts
o
k
a
,
“
L
i
n
k
p
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d
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c
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me
t
h
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s
a
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i
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c
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w
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k
s
a
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e
t
w
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r
k
me
t
r
i
c
s,
”
S
c
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n
t
i
f
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c
Pr
o
g
ra
m
m
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n
g
,
v
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l
.
2
0
1
5
,
p
p
.
1
–
1
3
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0
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5
,
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o
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:
1
0
.
1
1
5
5
/
2
0
1
5
/
1
7
2
8
7
9
.
[
2
]
W
.
C
u
k
i
e
r
sk
i
,
B
.
H
a
m
n
e
r
,
a
n
d
B
.
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a
n
g
,
“
G
r
a
p
h
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b
a
se
d
f
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a
t
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e
s
f
o
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l
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,
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T
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2
0
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1
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o
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N
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N
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k
s
,
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EEE,
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u
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4
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/
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JC
N
N
.
2
0
1
1
.
6
0
3
3
3
6
5
.
[
3
]
M
.
H
a
sa
n
e
t
a
l
.
,
“
L
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n
k
p
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d
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g
s
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p
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*
,
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S
D
M
0
6
:
w
o
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p
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l
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k
a
n
a
l
y
s
i
s,
c
o
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sm
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d
s
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c
u
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,
2
0
0
6
,
[
O
n
l
i
n
e
]
.
A
v
a
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l
a
b
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e
:
h
t
t
p
s:
/
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w
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2
7
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2
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9
2
9
1
.
[
4
]
T.
W
o
h
l
f
a
r
t
h
a
n
d
R
.
I
c
h
i
se
,
“
S
e
ma
n
t
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d
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t
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n
,
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n
I
n
t
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r
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t
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o
n
a
l
C
o
n
f
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n
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Pr
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Asp
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K
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M
a
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,
2
0
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p
p
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5
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–
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1
.
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:
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8
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4
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9
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4
7
-
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_
7
.
[
5
]
M
.
S
a
c
h
a
n
a
n
d
R
.
I
c
h
i
s
e
,
“
U
si
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g
s
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man
t
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