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h
e
s
p
r
ea
d
o
f
r
ad
ical
I
s
lam
ic
id
e
as
th
r
o
u
g
h
d
a
’
wah
web
s
ites
p
r
esen
ts
a
s
ig
n
if
ican
t
th
r
ea
t
to
th
e
in
teg
r
ity
a
n
d
s
tab
ilit
y
o
f
th
e
I
n
d
o
n
esian
n
atio
n
an
d
t
h
e
Un
itar
y
State
o
f
th
e
R
ep
u
b
lic
o
f
I
n
d
o
n
esia
(
NKRI)
.
T
h
er
e
f
o
r
e,
it
is
cr
u
cial
to
im
p
r
o
v
e
m
ed
ia
lit
er
ac
y
s
k
ills
am
o
n
g
Mu
s
lim
y
o
u
th
,
esp
ec
ially
I
s
lam
ic
ac
tiv
is
t
s
tu
d
en
ts
,
to
co
u
n
ter
th
e
in
f
l
u
en
ce
o
f
r
ad
ic
al
I
s
lam
ic
co
n
ten
t
d
is
s
em
in
ated
th
r
o
u
g
h
d
a
’
wa
h
web
s
ite
n
etwo
r
k
s
.
T
h
e
c
o
n
v
er
g
e
n
ce
o
f
we
b
s
ite
d
a
’
wah
an
d
th
e
r
is
e
o
f
r
ad
icalism
h
as
cr
ea
ted
a
co
m
p
lex
lan
d
s
ca
p
e
f
o
r
p
o
licy
m
ak
er
s
,
ed
u
ca
to
r
s
,
a
n
d
r
esear
ch
er
s
in
I
n
d
o
n
esia.
T
h
e
ex
ten
s
iv
e
u
s
e
o
f
p
latf
o
r
m
s
lik
e
W
eb
s
ite
Da
’
wah
h
as
n
o
t
o
n
ly
am
p
lifie
d
th
e
r
ea
ch
o
f
r
ad
ical
co
n
ten
t
b
u
t
h
as
also
f
ac
ilit
ated
th
e
r
ec
r
u
itm
en
t
an
d
r
ad
icaliza
tio
n
o
f
v
u
ln
er
a
b
le
in
d
iv
id
u
als.
T
h
is
p
h
en
o
m
en
o
n
is
p
ar
ticu
lar
ly
p
r
o
n
o
u
n
ce
d
i
n
I
n
d
o
n
esia,
wh
er
e
th
e
lar
g
e
Mu
s
li
m
p
o
p
u
latio
n
an
d
lo
w
m
e
d
ia
liter
ac
y
lev
els cr
ea
te
f
er
tile
g
r
o
u
n
d
f
o
r
th
e
s
p
r
ea
d
o
f
ex
tr
em
is
t
id
eo
lo
g
ies
[
1
1
]
.
T
h
e
I
n
d
o
n
esian
g
o
v
er
n
m
en
t
an
d
v
ar
io
u
s
n
o
n
-
g
o
v
er
n
m
en
tal
o
r
g
an
izatio
n
s
h
av
e
r
ec
o
g
n
ized
t
h
e
th
r
ea
t
p
o
s
ed
b
y
o
n
lin
e
r
ad
icalism
an
d
h
av
e
in
itiated
s
ev
er
al
co
u
n
ter
m
ea
s
u
r
es.
Ho
wev
e
r
,
th
e
r
ap
id
ev
o
lu
tio
n
o
f
web
s
ite
d
a
’
wah
tech
n
o
lo
g
ies
an
d
th
e
s
o
p
h
is
ticated
m
eth
o
d
s
em
p
lo
y
ed
b
y
r
ad
ical
g
r
o
u
p
s
n
ec
ess
itate
co
n
tin
u
o
u
s
ad
ap
tatio
n
an
d
im
p
r
o
v
em
e
n
t
o
f
th
ese
s
tr
ateg
ies.
E
f
f
o
r
ts
to
c
o
u
n
ter
r
ad
ical
c
o
n
t
en
t
o
n
we
b
s
ite
d
a
’
wah
m
u
s
t
b
e
m
u
lti
-
f
ac
eted
,
in
v
o
l
v
in
g
n
o
t
o
n
ly
tech
n
o
lo
g
ical
s
o
lu
tio
n
s
b
u
t
also
ed
u
ca
tio
n
al
an
d
co
m
m
u
n
ity
-
b
ased
ap
p
r
o
a
ch
es
[
1
2
]
.
E
n
h
an
ci
n
g
m
e
d
ia
liter
ac
y
is
a
cr
itical
co
m
p
o
n
en
t
o
f
t
h
ese
ef
f
o
r
ts
.
B
y
eq
u
ip
p
i
n
g
y
o
u
n
g
Mu
s
li
m
s
,
p
ar
ticu
lar
l
y
th
o
s
e
in
v
o
lv
ed
in
I
s
lam
ic
ac
tiv
is
m
,
with
th
e
s
k
ill
s
to
cr
itical
ly
an
aly
ze
an
d
in
ter
p
r
et
o
n
lin
e
co
n
ten
t,
it
is
p
o
s
s
ib
le
to
r
ed
u
ce
th
e
in
f
lu
en
ce
o
f
r
ad
ical
id
eo
lo
g
ies.
E
d
u
ca
tio
n
a
l
p
r
o
g
r
am
s
th
at
f
o
cu
s
o
n
cr
iti
ca
l
th
in
k
in
g
,
d
ig
ital
liter
ac
y
,
a
n
d
th
e
r
esp
o
n
s
ib
le
u
s
e
o
f
web
s
ite
d
a
’
wah
a
r
e
ess
en
tial in
b
u
ild
in
g
r
esil
ien
ce
ag
ain
s
t r
ad
icaliza
tio
n
[
1
1
]
,
[
1
3
]
.
Ad
d
itio
n
ally
,
c
o
llab
o
r
atio
n
b
e
twee
n
g
o
v
er
n
m
e
n
t
ag
e
n
cies,
ed
u
ca
tio
n
al
i
n
s
titu
tio
n
s
,
an
d
t
ec
h
n
o
lo
g
y
co
m
p
an
ies
is
v
ital
in
d
ev
elo
p
in
g
ef
f
ec
tiv
e
co
u
n
ter
-
r
ad
ical
izatio
n
s
tr
ateg
ies.
T
h
is
in
clu
d
es
m
o
n
ito
r
i
n
g
a
n
d
an
aly
zin
g
o
n
lin
e
co
n
ten
t,
id
e
n
tify
in
g
an
d
r
e
m
o
v
in
g
r
ad
ica
l
m
ater
ial,
an
d
p
r
o
m
o
tin
g
p
o
s
itiv
e
an
d
m
o
d
er
ate
n
ar
r
ativ
es
th
at
co
u
n
ter
ac
t
ex
tr
em
is
t
m
ess
ag
es.
R
e
s
ea
r
ch
p
lay
s
a
cr
u
cial
r
o
le
in
in
f
o
r
m
in
g
th
ese
ef
f
o
r
ts
[
1
4
]
.
B
y
u
tili
zin
g
tex
t
m
in
i
n
g
tec
h
n
iq
u
es
an
d
s
en
tim
en
t
a
n
aly
s
is
,
r
esear
ch
er
s
ca
n
g
ain
v
alu
a
b
le
in
s
ig
h
ts
in
to
th
e
n
atu
r
e
an
d
d
y
n
am
ics
o
f
r
ad
ica
l
co
n
ten
t
o
n
web
s
ite
d
a
’
wah
.
T
h
is
in
f
o
r
m
atio
n
ca
n
h
elp
in
d
ev
elo
p
in
g
tar
g
eted
in
ter
v
en
tio
n
s
th
at
ad
d
r
ess
th
e
s
p
ec
if
ic
n
ee
d
s
an
d
v
u
l
n
er
ab
ilit
ies
o
f
th
e
I
n
d
o
n
esian
Mu
s
lim
y
o
u
th
.
T
ec
h
n
o
lo
g
ical
ad
v
an
ce
m
e
n
ts
,
p
ar
ticu
l
ar
ly
th
e
I
n
ter
n
et,
h
av
e
b
ec
o
m
e
a
p
r
im
ar
y
n
ee
d
,
s
ig
n
if
ican
tly
ch
an
g
in
g
s
o
cieta
l
b
eh
av
io
r
g
lo
b
ally
[
1
3
]
.
T
h
e
I
n
te
r
n
et
h
as
d
is
s
o
lv
ed
g
eo
g
r
ap
h
ical
b
o
u
n
d
a
r
ies
an
d
r
ap
id
l
y
in
s
tig
ated
s
ig
n
if
ican
t
s
o
cial
ch
an
g
es.
H
o
wev
er
,
t
h
is
ad
v
an
ce
m
en
t
als
o
p
o
s
es
r
is
k
s
,
f
ac
ilit
atin
g
n
e
g
ativ
e
ac
tiv
ities
an
d
u
n
lawf
u
l
ac
tio
n
s
.
T
h
e
s
o
p
h
is
ticatio
n
o
f
th
is
tech
n
o
lo
g
y
ca
n
lead
in
d
i
v
id
u
als
to
ac
t
ag
ain
s
t
p
r
ev
ailin
g
s
o
cial
n
o
r
m
s
,
c
r
ea
tin
g
a
n
ew
g
lo
b
al
s
o
ciety
with
o
u
t
te
r
r
ito
r
ial
lim
itatio
n
s
.
Desp
ite
th
e
n
u
m
er
o
u
s
b
e
n
ef
its
o
f
in
f
o
r
m
atio
n
tech
n
o
lo
g
y
,
its
d
ar
k
s
id
e
h
as
s
ee
n
a
r
is
e
in
c
r
im
es
co
m
m
itted
th
r
o
u
g
h
tec
h
n
o
lo
g
ical
m
ea
n
s
.
On
e
s
u
ch
cr
im
e
is
cy
b
er
ter
r
o
r
is
m
,
wh
er
e
th
e
I
n
ter
n
et
is
m
is
u
s
ed
f
o
r
ter
r
o
r
is
t
ac
tiv
ities
.
C
y
b
er
ter
r
o
r
is
m
in
v
o
lv
es
p
o
liti
ca
lly
m
o
tiv
ate
d
attac
k
s
u
s
in
g
tech
n
o
lo
g
y
,
co
m
p
u
ter
n
etwo
r
k
s
,
an
d
tec
h
n
ic
al
in
f
r
astru
ctu
r
e
to
ca
u
s
e
h
ar
m
.
E
x
p
e
r
ts
ar
g
u
e
th
at
cy
b
er
ter
r
o
r
is
m
ca
n
b
e
m
o
r
e
d
an
g
er
o
u
s
th
an
tr
ad
itio
n
al
ter
r
o
r
is
m
[
5
]
,
[
1
5
]
.
T
h
e
r
is
e
o
f
o
n
lin
e
r
a
d
icaliza
tio
n
,
also
k
n
o
w
n
as
cy
b
er
-
ter
r
o
r
is
m
,
cy
b
er
-
r
ac
is
m
,
o
r
cy
b
er
h
ate,
h
as
b
ec
o
m
e
a
s
ig
n
if
ican
t c
o
n
ce
r
n
f
o
r
co
m
m
u
n
ities
,
g
o
v
er
n
m
en
ts
,
an
d
law
en
f
o
r
ce
m
e
n
t a
g
en
cies w
o
r
l
d
wid
e
[
1
6
]
.
C
y
b
er
r
ac
is
m
is
a
ty
p
e
o
f
cy
b
er
cr
im
e
ch
a
r
ac
ter
ized
b
y
r
ad
ic
al
b
eh
av
i
o
r
,
wh
ich
v
ar
ies
ac
r
o
s
s
n
atio
n
s
an
d
is
a
to
p
ic
o
f
m
u
ltid
is
cip
lin
ar
y
r
esear
ch
.
R
ad
ical
co
n
t
en
t,
wh
ich
in
cites
v
io
le
n
ce
,
s
p
r
ea
d
s
h
atr
ed
,
an
d
p
r
o
m
o
tes
an
ti
-
n
atio
n
alis
m
,
is
o
f
p
ar
ticu
lar
co
n
ce
r
n
.
Fo
r
B
NPT,
r
ad
ical
co
n
ten
t
in
clu
d
es
a
d
v
o
ca
tin
g
v
io
len
ce
in
th
e
n
am
e
o
f
r
elig
io
n
,
in
ter
p
r
etin
g
jih
ad
as
s
u
icid
e
b
o
m
b
i
n
g
,
an
d
d
e
n
o
u
n
cin
g
o
th
er
s
as
in
f
id
els.
T
h
e
cr
iter
ia
f
o
r
r
a
d
icalism,
ac
co
r
d
in
g
to
B
NPT,
in
clu
d
e:
a)
Ad
v
o
ca
tin
g
r
ap
id
c
h
an
g
e
t
h
r
o
u
g
h
v
i
o
len
ce
in
t
h
e
n
am
e
o
f
r
e
lig
io
n
.
b)
Den
o
u
n
cin
g
o
th
e
r
s
as in
f
id
els.
c)
Su
p
p
o
r
tin
g
,
s
p
r
ea
d
i
n
g
,
a
n
d
in
v
itin
g
o
th
er
s
to
jo
in
I
SIS/I
S.
d)
I
n
ter
p
r
etin
g
jih
ad
n
ar
r
o
wly
.
R
esear
ch
er
s
f
ac
e
ch
allen
g
es
in
d
etec
tin
g
r
ad
ical
o
n
lin
e
co
n
ten
t
d
u
e
t
o
th
e
lar
g
e
v
o
lu
m
e
o
f
u
n
s
tr
u
ctu
r
ed
,
u
s
er
-
g
en
er
ated
co
n
ten
t
th
at
ch
a
n
g
es
d
y
n
am
ic
ally
.
T
h
e
s
ec
r
etiv
e
n
atu
r
e
o
f
r
ad
ical
co
n
ten
t
also
co
m
p
licates
d
etec
tio
n
,
m
ak
i
n
g
tr
ad
itio
n
al
web
cr
awle
r
s
in
ef
f
ec
tiv
e.
Stu
d
ie
s
s
u
g
g
est
u
s
i
n
g
T
e
x
t
Min
in
g
a
n
d
W
eb
Scr
ap
in
g
m
eth
o
d
s
to
cla
s
s
if
y
r
ad
ical
co
n
ten
t
[
1
7
]
.
R
esear
ch
h
as
s
h
o
wn
th
at
v
ar
io
u
s
I
n
ter
n
et
p
latf
o
r
m
s
ca
n
b
e
ea
s
ily
m
is
u
s
ed
f
o
r
h
ar
m
f
u
l p
u
r
p
o
s
es,
f
o
r
m
i
n
g
h
ate
g
r
o
u
p
s
,
s
p
r
ea
d
i
n
g
ex
tr
e
m
is
t id
eo
lo
g
ies,
an
d
in
citin
g
v
io
len
ce
.
Dev
el
o
p
ed
a
s
y
s
tem
to
d
etec
t
u
s
er
s
ac
ce
s
s
in
g
ter
r
o
r
is
t
web
s
ites
b
y
m
o
n
ito
r
in
g
an
d
an
al
y
zin
g
we
b
co
n
ten
t
in
r
ea
l
-
tim
e
[
1
8
]
.
A
n
o
th
er
s
tu
d
y
b
y
[
1
9
]
p
r
o
p
o
s
ed
an
ef
f
icien
t
al
g
o
r
ith
m
t
o
d
estab
ilize
ter
r
o
r
is
t
n
etwo
r
k
s
b
y
u
n
co
v
e
r
in
g
h
id
d
e
n
h
ier
ar
c
h
ies
with
in
th
ese
n
etwo
r
k
s
u
s
in
g
s
o
cial
n
etwo
r
k
an
aly
s
is
.
I
n
tr
o
d
u
ce
d
a
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J I
n
f
&
C
o
m
m
u
n
T
ec
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n
o
l
I
SS
N:
2252
-
8
7
7
6
A
n
a
lyzi
n
g
r
a
d
ica
lis
m
s
en
timen
ts
in
I
n
d
o
n
esia
n
d
a
'wa
h
co
n
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n
w
eb
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ite
d
a
’
w
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h
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o
u
g
… (
A
u
lia
A
z
iz
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)
577
s
em
i
-
au
to
m
atic
ap
p
r
o
ac
h
f
o
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d
etec
tin
g
r
ad
ical
co
n
ten
t
u
s
in
g
th
e
lin
k
-
b
ased
b
o
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ts
tr
ap
(
L
B
B
)
alg
o
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ith
m
,
wh
ich
id
en
tifie
s
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d
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p
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d
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th
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tativ
e
UR
L
s
to
ca
p
tu
r
e
r
elate
d
r
ad
ical
co
n
ten
t.
I
n
co
n
clu
s
io
n
,
th
e
in
ter
s
ec
tio
n
o
f
web
s
ite
d
a
’
wah
a
n
d
r
ad
icalism
p
r
esen
ts
a
s
ig
n
if
ican
t
ch
alle
n
g
e
f
o
r
I
n
d
o
n
esia.
Ad
d
r
ess
in
g
th
is
is
s
u
e
r
eq
u
ir
es
a
co
m
p
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h
e
n
s
iv
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ap
p
r
o
ac
h
th
at
co
m
b
in
es
tech
n
o
lo
g
ical,
ed
u
ca
tio
n
al,
an
d
co
m
m
u
n
i
ty
-
b
ased
s
tr
ateg
ies.
E
n
h
an
cin
g
m
ed
ia
liter
ac
y
,
f
o
s
ter
in
g
co
llab
o
r
atio
n
,
an
d
lev
er
ag
in
g
r
esear
ch
a
r
e
k
ey
ele
m
en
ts
in
th
e
f
ig
h
t
ag
ain
s
t o
n
lin
e
r
a
d
icalism,
en
s
u
r
in
g
th
e
s
tab
ilit
y
an
d
in
teg
r
ity
o
f
I
n
d
o
n
esian
s
o
ciety
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
m
eth
o
d
s
an
d
tech
n
iq
u
es
u
s
ed
in
th
is
r
esear
ch
ex
p
lai
n
th
e
s
tep
s
o
r
p
r
o
ce
s
s
o
f
d
e
v
elo
p
in
g
a
n
ap
p
licatio
n
f
o
r
d
etec
tin
g
r
a
d
ical
co
n
ten
t.
T
h
is
ap
p
licatio
n
h
e
lp
s
u
s
er
s
id
en
tify
r
ad
ical
an
d
n
o
n
-
r
a
d
ical
co
n
ten
t
in
I
n
d
o
n
esia.
T
h
e
s
y
s
tem
d
esi
g
n
f
o
r
th
is
r
esear
ch
is
s
h
o
wn
i
n
Fig
u
r
e
1
.
Fig
u
r
e
1
.
R
ad
ical
co
n
ten
t r
ese
ar
ch
s
y
s
tem
d
esig
n
As
s
h
o
wn
in
Fig
u
r
e
1
,
th
e
s
y
s
tem
wo
r
k
f
lo
w
s
tar
ts
b
y
g
ath
er
in
g
n
ews
co
n
ten
t
d
ata
f
r
o
m
t
h
e
m
in
is
tr
y
o
f
co
m
m
u
n
icatio
n
a
n
d
i
n
f
o
r
m
at
io
n
’
s
ap
p
r
o
v
ed
in
ter
n
et
s
o
u
r
ce
s
.
Nex
t,
web
c
o
n
ten
t
e
x
tr
ac
tio
n
r
em
o
v
es
HT
ML
tag
s
,
leav
in
g
o
n
ly
th
e
t
ex
t.
T
h
en
,
tex
t m
i
n
in
g
id
e
n
tifie
s
k
ey
wo
r
d
s
th
r
o
u
g
h
s
ev
er
al
s
tag
es: ca
s
e
f
o
ld
in
g
,
to
k
en
izatio
n
,
f
ilter
in
g
,
s
tem
m
i
n
g
,
tag
g
i
n
g
,
an
d
an
aly
zi
n
g
,
w
h
ich
r
esu
lt
in
a
s
et
o
f
k
ey
w
o
r
d
s
[
2
0
]
,
[
2
1
]
.
T
h
ese
k
ey
wo
r
d
s
ar
e
s
to
r
e
d
in
a
d
atab
ase
an
d
u
s
ed
f
o
r
f
ea
tu
r
e
s
elec
tio
n
to
r
ed
u
ce
d
ata
d
im
en
s
io
n
ality
.
T
h
e
class
if
icatio
n
p
r
o
ce
s
s
f
o
llo
ws,
d
eter
m
in
i
n
g
w
h
ich
k
ey
wo
r
d
s
co
r
r
esp
o
n
d
to
class
lab
el
s
p
r
o
v
i
d
e
d
b
y
t
h
e
m
in
is
tr
y
o
f
co
m
m
u
n
icatio
n
an
d
in
f
o
r
m
atio
n
.
W
eb
m
in
in
g
ap
p
lies
d
ata
m
in
in
g
tech
n
iq
u
es
to
an
al
y
ze
web
d
ata
an
d
ex
tr
ac
t
m
ea
n
in
g
f
u
l
in
f
o
r
m
atio
n
.
I
t
aim
s
to
tr
an
s
f
o
r
m
lar
g
e
am
o
u
n
ts
o
f
web
d
a
ta
in
to
ac
tio
n
ab
le
in
s
ig
h
ts
.
I
n
th
e
co
n
tex
t
o
f
th
is
s
y
s
tem
,
web
m
in
in
g
is
k
ey
f
o
r
p
r
o
ce
s
s
in
g
an
d
id
en
tify
in
g
p
a
tter
n
s
in
th
e
ex
tr
ac
ted
tex
t
d
ata.
W
eb
m
in
in
g
ca
n
b
e
ca
teg
o
r
ized
in
to
th
r
ee
ty
p
e
s
:
co
n
ten
t
m
in
in
g
,
s
tr
u
ctu
r
e
m
in
in
g
,
an
d
u
s
ag
e
m
in
in
g
.
C
o
n
t
en
t
m
in
in
g
e
x
tr
ac
ts
v
alu
ab
le
d
ata
f
r
o
m
web
d
o
c
u
m
en
ts
u
s
in
g
tech
n
iq
u
es
lik
e
NL
P,
I
R
,
an
d
ML
.
Stru
ctu
r
e
m
in
in
g
an
aly
ze
s
h
y
p
er
lin
k
r
elatio
n
s
h
ip
s
to
im
p
r
o
v
e
p
ag
e
r
a
n
k
in
g
a
n
d
n
a
v
i
g
atio
n
.
Usag
e
m
in
in
g
f
o
cu
s
es
o
n
an
aly
zin
g
web
lo
g
s
to
u
n
d
er
s
tan
d
u
s
er
b
eh
av
i
o
r
an
d
im
p
r
o
v
e
p
e
r
s
o
n
aliza
tio
n
an
d
a
d
ap
tab
ilit
y
.
T
h
e
web
m
in
in
g
p
r
o
ce
s
s
in
clu
d
es
d
ata
co
llectio
n
,
p
r
e
p
r
o
ce
s
s
in
g
,
p
atter
n
d
is
co
v
er
y
,
e
v
al
u
atio
n
,
an
d
d
ep
lo
y
m
e
n
t
[
2
2
]
.
Data
s
o
u
r
ce
s
in
clu
d
e
web
p
a
g
e
s
,
lo
g
s
,
an
d
u
s
er
p
r
o
f
iles
,
with
p
r
e
p
r
o
ce
s
s
in
g
in
v
o
lv
in
g
d
at
a
clea
n
in
g
an
d
tr
a
n
s
f
o
r
m
atio
n
[
2
3
]
.
A
f
ter
ap
p
ly
in
g
m
in
in
g
al
g
o
r
ith
m
s
to
d
is
co
v
er
p
atter
n
s
,
th
ese
in
s
ig
h
ts
ar
e
ev
alu
ated
a
n
d
u
s
ed
in
r
ea
l
-
w
o
r
ld
a
p
p
licatio
n
s
.
Desp
ite
its
p
o
ten
tial,
web
m
in
in
g
f
ac
es
ch
allen
g
es
s
u
c
h
as
in
co
n
s
is
ten
t,
n
o
is
y
d
ata,
th
e
n
ee
d
f
o
r
s
ca
lab
le
tech
n
iq
u
es,
p
r
iv
ac
y
co
n
ce
r
n
s
,
a
n
d
t
h
e
d
y
n
am
ic
n
atu
r
e
o
f
th
e
web
[
2
4
]
.
Nev
er
t
h
eless
,
it
r
em
ain
s
a
p
o
wer
f
u
l
to
o
l
f
o
r
en
h
an
cin
g
we
b
s
er
v
ices
an
d
u
s
er
ex
p
er
ie
n
ce
s
[
2
5
]
.
T
ex
t m
in
in
g
,
a
p
p
ly
in
g
d
ata
m
i
n
in
g
to
tex
t d
ata,
e
x
tr
ac
ts
p
atter
n
s
f
r
o
m
u
n
s
tr
u
ctu
r
e
d
tex
t b
y
co
n
v
er
tin
g
it in
to
a
s
tr
u
ctu
r
ed
f
o
r
m
at
s
u
itab
le
f
o
r
an
aly
s
is
[
2
6
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
7
6
I
n
t J
I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
,
Vo
l.
14
,
No
.
2
,
A
u
g
u
s
t
20
25
:
575
-
585
578
A.
Key
p
r
ep
r
o
ce
s
s
in
g
s
tep
s
:
−
C
ase
f
o
ld
in
g
Def
in
itio
n
:
c
ase
f
o
ld
in
g
is
th
e
p
r
o
ce
s
s
o
f
c
o
n
v
e
r
tin
g
all
ch
a
r
ac
ter
s
in
a
tex
t
d
o
cu
m
en
t
t
o
a
s
tan
d
ar
d
ca
s
e,
u
s
u
ally
lo
wer
ca
s
e.
T
h
is
s
tep
en
s
u
r
es
co
n
s
is
ten
cy
in
te
x
t
p
r
o
ce
s
s
in
g
s
in
ce
tex
t
d
o
cu
m
en
ts
m
ay
n
o
t
u
s
e
ca
p
ital le
tter
s
co
n
s
is
ten
tly
.
−
T
o
k
en
izatio
n
T
o
k
en
izatio
n
is
th
e
p
r
o
ce
s
s
o
f
d
i
v
id
in
g
th
e
in
p
u
t
te
x
t
i
n
to
in
d
i
v
id
u
al
w
o
r
d
s
o
r
to
k
en
s
,
wh
ile
r
em
o
v
in
g
p
u
n
ctu
atio
n
,
n
u
m
b
er
s
,
an
d
n
o
n
-
alp
h
ab
etic
c
h
ar
a
cter
s
,
wh
ich
s
er
v
e
as
d
elim
iter
s
an
d
d
o
n
o
t
a
d
d
v
alu
e
in
tex
t
p
r
o
ce
s
s
in
g
.
Fo
r
e
x
am
p
le,
t
h
e
s
en
ten
ce
“
T
ex
t
m
in
in
g
,
also
k
n
o
wn
as
te
x
t
an
al
y
tics
,
is
v
alu
ab
le.
”
wo
u
ld
b
e
to
k
en
ized
in
to
[
“
tex
t
”
,
“
m
in
in
g
”
,
“
also
”
,
“
k
n
o
wn
”
,
“
as
”
,
“
tex
t
”
,
“
an
aly
tics
”
,
“
is
”
,
“
v
alu
ab
le
”
].
−
Fil
ter
in
g
Fil
ter
in
g
in
v
o
l
v
es
s
elec
tin
g
s
ig
n
if
ican
t
wo
r
d
s
f
r
o
m
th
e
to
k
en
s
cr
ea
ted
d
u
r
in
g
to
k
en
i
za
tio
n
b
y
elim
in
atin
g
co
m
m
o
n
wo
r
d
s
,
k
n
o
wn
as
s
to
p
wo
r
d
s
,
th
at
d
o
n
o
t
p
r
o
v
id
e
m
ea
n
in
g
f
u
l
c
o
n
ten
t,
s
u
ch
as
“
is
”
,
“
th
e
”
,
an
d
“
a
n
d
”
.
Fo
r
in
s
tan
ce
,
f
r
o
m
t
h
e
to
k
e
n
s
[
“
tex
t
”
,
“
m
i
n
in
g
”
,
“
also
”
,
“
k
n
o
wn
”
,
“
as
”
,
“
tex
t
”
,
“
an
aly
tics
”
,
“
is
”
,
“
v
alu
ab
le
”
]
,
th
e
s
to
p
wo
r
d
s
“
also
”
,
“
as
”
,
an
d
“
is
”
wo
u
l
d
b
e
r
em
o
v
ed
.
−
Stem
m
in
g
Stem
m
in
g
r
ef
er
s
to
th
e
p
r
o
ce
s
s
o
f
r
ed
u
cin
g
wo
r
d
s
to
th
eir
r
o
o
t
f
o
r
m
to
s
tan
d
ar
d
ize
v
ar
iatio
n
s
o
f
wo
r
d
s
,
im
p
r
o
v
in
g
th
e
ef
f
icien
cy
o
f
tex
t
m
in
i
n
g
.
T
h
is
s
tep
c
o
n
v
er
ts
in
f
lecte
d
o
r
d
er
i
v
ed
w
o
r
d
s
in
to
th
eir
b
ase
f
o
r
m
.
C
o
m
m
o
n
s
tem
m
in
g
alg
o
r
ith
m
s
in
clu
d
e
th
e
Po
r
ter
Stem
m
er
f
o
r
E
n
g
lis
h
an
d
Ar
if
in
-
Setio
n
o
Stem
m
er
f
o
r
I
n
d
o
n
esian
.
Fo
r
ex
a
m
p
le,
th
e
wo
r
d
s
“
r
u
n
n
in
g
”
,
“
r
u
n
s
”
,
a
n
d
“
r
an
”
wo
u
ld
b
e
r
e
d
u
ce
d
to
th
e
r
o
o
t w
o
r
d
“
r
u
n
”
.
−
T
ag
g
in
g
T
ag
g
in
g
is
th
e
s
tep
o
f
ass
ig
n
i
n
g
lab
els
o
r
ca
teg
o
r
ies
to
wo
r
d
s
,
u
s
u
ally
af
ter
s
tem
m
in
g
,
to
id
en
tify
th
eir
p
ar
t
o
f
s
p
ee
ch
o
r
o
th
er
s
e
m
an
tic
p
r
o
p
e
r
ties
.
T
h
is
h
elp
s
to
f
u
r
th
er
clar
i
f
y
th
e
r
o
le
o
f
ea
ch
wo
r
d
with
in
th
e
co
n
tex
t o
f
th
e
tex
t.
−
An
aly
zin
g
Def
in
itio
n
:
a
n
aly
zi
n
g
d
eter
m
i
n
es
th
e
r
elatio
n
s
h
ip
s
b
etwe
en
wo
r
d
s
ac
r
o
s
s
d
o
c
u
m
en
ts
.
T
h
e
s
im
p
lest
alg
o
r
ith
m
f
o
r
s
co
r
in
g
in
tex
t
m
in
in
g
is
ter
m
f
r
e
q
u
en
c
y
-
in
v
er
s
e
d
o
cu
m
e
n
t
f
r
e
q
u
en
c
y
(
TF
-
I
DF
)
.
E
x
am
p
le:
c
alcu
latin
g
th
e
T
F
-
ID
F
s
co
r
es
f
o
r
wo
r
d
s
in
a
d
o
cu
m
en
t
h
el
p
s
id
en
tify
th
e
im
p
o
r
tan
ce
o
f
ea
ch
wo
r
d
r
elativ
e
to
th
e
d
o
cu
m
en
t c
o
r
p
u
s
.
B.
C
las
s
if
icatio
n
Def
in
itio
n
:
c
lass
if
icatio
n
is
a
d
ata
m
in
in
g
tech
n
iq
u
e
u
s
ed
t
o
s
o
lv
e
r
ea
l
-
wo
r
l
d
p
r
o
b
lem
s
b
y
lear
n
in
g
p
atter
n
s
f
r
o
m
h
is
to
r
ical
d
ata
t
o
ca
teg
o
r
ize
n
ew
in
s
tan
ce
s
in
t
o
p
r
ed
ef
in
e
d
g
r
o
u
p
s
o
r
class
es.
Me
th
o
d
o
lo
g
y
:
t
h
e
ty
p
ical
two
-
s
tep
p
r
o
ce
s
s
in
cl
u
d
es
‘
m
o
d
el
d
ev
elo
p
m
en
t/tra
in
in
g
’
f
o
llo
wed
b
y
‘
m
o
d
el
t
esti
n
g
/d
ep
lo
y
m
en
t
’
.
Fo
r
ex
am
p
le,
alg
o
r
ith
m
s
lik
e
K
-
n
ea
r
est
n
eig
h
b
o
r
s
(
K
-
NN)
,
d
ec
is
io
n
tr
ee
s
,
a
n
d
o
th
er
s
a
r
e
u
s
ed
to
class
if
y
d
ata.
T
h
e
K
-
NN
alg
o
r
ith
m
cl
ass
if
ies
n
ew
d
ata
b
ased
o
n
its
s
im
ilar
ity
to
lab
eled
d
ata,
u
s
u
ally
m
ea
s
u
r
ed
b
y
E
u
clid
ea
n
d
is
tan
ce
.
T
h
r
o
u
g
h
tex
t
m
in
in
g
,
t
h
ese
p
r
ep
r
o
ce
s
s
in
g
an
d
class
if
icatio
n
s
tep
s
co
n
v
er
t
u
n
s
tr
u
ctu
r
e
d
tex
t
d
ata
in
to
s
tr
u
ctu
r
ed
,
v
alu
a
b
le
in
s
ig
h
ts
th
at
ca
n
b
e
ap
p
lie
d
in
ar
ea
s
s
u
ch
as
b
u
s
in
ess
in
tellig
en
ce
,
cu
s
to
m
er
s
en
tim
en
t a
n
aly
s
is
,
an
d
m
o
r
e.
I
n
th
is
r
esear
ch
,
t
h
e
r
esear
c
h
an
d
d
ev
elo
p
m
en
t
(
R
&
D)
m
eth
o
d
is
u
s
ed
,
wh
ich
is
a
s
y
s
tem
atic
ap
p
r
o
ac
h
a
im
e
d
at
im
p
r
o
v
in
g
o
r
d
ev
elo
p
i
n
g
n
ew
p
r
o
d
u
cts
t
h
r
o
u
g
h
r
ig
o
r
o
u
s
test
in
g
to
en
s
u
r
e
th
ei
r
r
eliab
ilit
y
.
T
h
e
s
tu
d
y
p
r
esen
ts
th
eo
r
ies
an
d
co
n
ce
p
ts
r
elev
an
t
to
th
e
p
r
o
b
lem
an
d
s
co
p
e
o
f
th
e
d
is
cu
s
s
io
n
,
d
r
awin
g
o
n
r
ef
er
en
ce
s
f
r
o
m
d
i
v
er
s
e
f
ield
s
s
u
ch
as
p
o
liti
cs,
s
o
c
io
lo
g
y
,
c
u
ltu
r
e,
ec
o
n
o
m
ics,
an
d
in
f
o
r
m
atio
n
tech
n
o
lo
g
y
.
T
h
e
r
esear
ch
e
x
p
lo
r
es
f
u
n
d
a
m
en
tal
an
d
r
ad
ical
d
ef
i
n
itio
n
s
f
r
o
m
th
ese
p
e
r
s
p
ec
tiv
es,
alo
n
g
with
s
en
tim
en
t
an
aly
s
is
an
d
tex
t
m
in
in
g
th
eo
r
ies.
Fu
r
th
er
m
o
r
e,
th
e
co
n
ce
p
t
o
f
f
u
n
d
am
e
n
talis
m
,
o
f
ten
ass
o
ciate
d
with
r
ev
iv
alis
t
r
elig
io
u
s
g
r
o
u
p
s
,
is
d
is
cu
s
s
ed
,
alo
n
g
with
r
ad
ica
lis
m
,
b
o
th
o
f
wh
ich
ca
n
in
v
o
lv
e
v
io
len
ce
as
a
m
ea
n
s
o
f
ac
h
iev
in
g
o
b
jectiv
es
r
o
o
ted
in
r
elig
io
u
s
b
elief
s
.
T
h
e
p
ap
er
r
ev
iews
v
ar
io
u
s
u
n
d
er
s
tan
d
in
g
s
f
r
o
m
m
u
ltip
le
v
iewp
o
in
ts
to
p
r
o
v
i
d
e
a
co
m
p
r
e
h
en
s
iv
e
f
r
am
ewo
r
k
f
o
r
th
e
s
tu
d
y
s
h
o
w
in
th
e
T
ab
l
e
1
.
R
ad
icalism
o
f
ten
ar
is
es
as
a
r
ea
ctio
n
to
in
ju
s
tice
an
d
th
e
u
n
eq
u
al
d
is
tr
ib
u
tio
n
o
f
p
o
wer
in
s
o
ciety
.
Po
liti
ca
lly
,
it
r
ep
r
esen
ts
th
e
u
s
e
o
f
s
tate
p
o
wer
b
y
in
d
iv
i
d
u
als
o
r
g
r
o
u
p
s
to
ac
h
iev
e
s
p
ec
if
ic
o
b
jectiv
es.
So
cio
lo
g
ically
,
c
o
n
f
lict
th
e
o
r
y
s
u
g
g
ests
th
at
r
a
d
icalism
e
m
er
g
es
f
r
o
m
th
e
co
n
ce
n
tr
ati
o
n
o
f
p
o
wer
a
m
o
n
g
ce
r
tain
g
r
o
u
p
s
,
wh
o
s
ee
k
to
m
ain
tain
th
eir
d
o
m
in
an
ce
.
A
n
th
r
o
p
o
lo
g
ically
,
r
ad
icalism
is
s
ee
n
as
a
s
o
cial
s
y
s
tem
d
ev
elo
p
ed
b
y
g
r
o
u
p
s
to
d
ef
e
n
d
a
g
ain
s
t
p
er
ce
i
v
ed
t
h
r
ea
ts
.
E
co
n
o
m
ically
,
r
ad
ical
ac
ts
ar
e
o
f
ten
v
iewe
d
as
r
esis
tan
ce
b
y
m
ar
g
in
alize
d
g
r
o
u
p
s
a
g
ain
s
t
th
e
r
u
lin
g
class
an
d
s
tate,
s
ee
n
as
f
a
ilu
r
es
in
p
r
o
v
id
in
g
p
r
o
s
p
er
ity
.
I
n
r
elig
io
u
s
co
n
te
x
ts
,
r
ad
icalism
is
o
f
ten
f
u
eled
b
y
n
ar
r
o
w
in
ter
p
r
etatio
n
s
o
f
r
elig
io
u
s
teac
h
in
g
s
,
s
u
ch
as
th
e
m
is
ap
p
licatio
n
o
f
jih
ad
t
o
ju
s
tify
v
io
len
ce
.
I
n
i
n
f
o
r
m
atio
n
tech
n
o
lo
g
y
,
r
ad
ic
al
co
n
ten
t
ty
p
ically
in
v
o
lv
es
p
r
o
m
o
tin
g
v
io
len
ce
,
h
ate,
an
d
an
ti
-
n
atio
n
alis
m
.
Fro
m
th
ese
p
e
r
s
p
ec
tiv
es,
r
ad
ical
f
ea
tu
r
es
ar
e
id
en
tifie
d
to
d
etec
t a
n
d
a
n
aly
z
e
r
ad
ical
co
n
ten
t
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J I
n
f
&
C
o
m
m
u
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T
ec
h
n
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I
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N:
2252
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8
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6
A
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a
lyzi
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a
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ica
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I
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o
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d
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'wa
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A
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579
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u
r
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2
,
th
e
s
y
s
tem
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alu
ates
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ilar
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etwe
en
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ata
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ase
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ased
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ical
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p
r
o
ce
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in
v
o
lv
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ev
er
al
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ta
g
es:
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tar
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atu
r
e
r
ev
iew,
g
ath
er
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g
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ata
o
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ad
ical
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n
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t
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r
ep
r
o
ce
s
s
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g
th
r
o
u
g
h
tex
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m
i
n
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g
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e
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o
n
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t
in
to
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es,
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d
s
elec
tin
g
r
elev
a
n
t
f
ea
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r
es.
T
h
e
f
in
al
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lt
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m
o
d
el
th
a
t
ca
teg
o
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izes
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ical
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n
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ac
co
r
d
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g
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e
ch
a
r
ac
ter
is
tics
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d
d
ef
in
itio
n
s
o
f
r
ad
icalism
in
I
n
d
o
n
esia.
T
ab
le
1
.
Var
io
u
s
asp
ec
t f
o
r
r
e
v
iews d
ef
in
itio
n
o
f
r
ad
icalism
V
a
r
i
o
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s
a
sp
e
c
t
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ased
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t
i
o
n
s,
m
o
b
i
l
i
z
a
t
i
o
n
o
f
f
u
n
d
s,
a
n
d
p
e
o
p
l
e
2.
Y
e
l
l
o
w
C
a
l
l
s f
o
r
a
c
e
r
t
a
i
n
a
t
t
i
t
u
d
e
,
p
r
o
v
o
c
a
t
i
o
n
3.
G
r
e
e
n
S
p
r
e
a
d
i
n
g
f
a
l
se
n
e
w
s a
b
o
u
t
c
e
r
t
a
i
n
g
r
o
u
p
s
4.
W
h
i
t
e
N
o
r
mal
c
o
n
t
e
n
t
T
h
e
d
ec
is
io
n
-
m
a
k
in
g
p
r
o
ce
s
s
in
th
is
m
eth
o
d
i
n
v
o
l
v
es
ev
a
lu
atin
g
test
d
ata
b
y
c
o
m
p
ar
i
n
g
it
to
all
tr
ain
in
g
d
ata
u
s
in
g
th
e
E
u
cli
d
ea
n
d
is
tan
ce
to
m
ea
s
u
r
e
th
eir
p
r
o
x
im
ity
.
T
h
ese
d
is
tan
c
es
ar
e
r
an
k
ed
f
r
o
m
s
m
allest
to
lar
g
est,
an
d
a
v
o
tin
g
s
y
s
tem
is
ap
p
lied
b
ased
o
n
th
e
r
an
k
e
d
d
is
tan
ce
s
.
T
h
e
n
u
m
b
er
o
f
v
o
tes,
d
en
o
ted
b
y
k
in
th
e
KNN
alg
o
r
ith
m
,
is
u
s
u
ally
s
et
to
an
o
d
d
n
u
m
b
er
s
u
ch
as
1
,
3
,
5
,
o
r
7
to
av
o
i
d
ties
.
T
h
e
class
if
icatio
n
o
f
th
e
test
d
ata
is
d
eter
m
in
ed
b
y
th
e
m
a
jo
r
ity
v
o
te
f
r
o
m
th
e
n
ea
r
est
n
eig
h
b
o
r
s
.
E
ac
h
test
d
ata
p
o
i
n
t
is
ass
ig
n
ed
a
lab
e
l
th
r
o
u
g
h
th
e
KNN
al
g
o
r
ith
m
.
T
h
e
s
y
s
tem
th
en
s
ea
r
ch
es
f
o
r
d
ata
b
y
u
s
in
g
k
ey
wo
r
d
s
f
r
o
m
th
e
d
atab
ase
a
n
d
ca
lcu
lates
th
e
E
u
clid
ea
n
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i
s
tan
ce
f
o
r
ea
ch
wo
r
d
.
T
h
e
f
i
n
al
r
esu
lt
is
a
la
b
el
(
r
ed
,
y
ello
w,
g
r
ee
n
,
o
r
w
h
ite
)
.
T
h
e
alg
o
r
i
th
m
’
s
ac
cu
r
ac
y
is
ev
alu
ated
b
y
u
s
in
g
a
r
ad
ical
d
ataset,
d
iv
id
ed
in
to
v
ar
io
u
s
d
ec
is
io
n
-
m
ak
in
g
attr
ib
u
tes.
T
h
e
s
y
s
tem
was
d
e
v
elo
p
ed
wi
th
a
web
s
cr
ap
in
g
ap
p
licatio
n
,
an
d
th
e
s
tu
d
y
in
cl
u
d
es
a
f
lo
wch
ar
t
f
o
r
th
e
test
s
co
n
d
u
cted
.
E
x
p
er
im
en
tal
p
ar
am
eter
s
in
clu
d
e
t
h
e
q
u
er
y
r
esu
lts
,
class
if
icatio
n
ac
cu
r
ac
y
(
m
ea
s
u
r
e
d
u
s
in
g
th
e
co
n
f
u
s
io
n
m
atr
ix
)
,
a
n
d
p
er
f
o
r
m
an
ce
in
ter
m
s
o
f
p
r
o
ce
s
s
in
g
tim
e.
T
h
e
e
x
p
er
im
e
n
ts
ar
e
d
iv
i
d
ed
in
to
th
r
ee
m
ain
test
s
:
q
u
er
y
in
g
t
h
e
s
y
s
tem
,
ev
alu
atin
g
class
if
icatio
n
ac
cu
r
ac
y
,
a
n
d
ass
ess
in
g
s
y
s
tem
p
er
f
o
r
m
an
ce
in
p
r
o
ce
s
s
in
g
tim
e
a
n
d
m
e
m
o
r
y
u
s
ag
e.
T
h
e
r
etr
iev
al
o
f
n
ews
co
n
ten
t
f
r
o
m
d
a
’
wah
web
s
ite
s
,
s
u
ch
as
W
eb
s
ite
Da
’
wah
,
was
ca
r
r
ied
o
u
t
th
r
o
u
g
h
s
cr
ip
ts
.
Fo
r
th
is
ex
p
er
i
m
en
t,
h
o
we
v
er
,
th
e
n
ews
co
n
ten
t
was
d
ir
ec
tly
s
o
u
r
ce
d
f
r
o
m
th
e
s
cr
ap
p
ed
d
at
ab
ase
o
f
W
eb
s
ite
Da
’
wah
co
n
t
en
t.
Data
test
in
g
is
co
n
d
u
cted
d
ir
e
ctly
b
y
th
e
s
y
s
tem
,
b
eg
in
n
in
g
with
tex
t
m
in
in
g
to
ex
tr
ac
t
s
ig
n
if
ican
t
wo
r
d
s
f
r
o
m
t
h
e
n
ews
co
n
ten
t.
T
h
is
p
r
o
ce
s
s
is
s
im
ilar
to
th
e
tr
ain
in
g
p
r
o
ce
d
u
r
e
d
escr
ib
e
d
ea
r
lier
.
Ho
wev
er
,
u
n
lik
e
th
e
tr
ai
n
in
g
p
r
o
ce
s
s
,
w
h
ich
in
clu
d
es
a
f
ea
tu
r
e
s
elec
ti
o
n
s
tep
af
ter
te
x
t
m
in
in
g
,
th
e
t
esti
n
g
p
r
o
ce
s
s
d
o
es
n
o
t.
I
n
s
tead
,
th
e
test
ed
d
ata
is
s
to
r
ed
in
th
e
d
atab
ase
alo
n
g
s
id
e
th
e
tr
ain
in
g
d
ata
f
o
r
class
if
icatio
n
.
T
h
e
s
y
s
tem
test
s
th
e
s
ea
r
ch
d
ata
with
th
e
k
ey
wo
r
d
s
s
to
r
ed
i
n
th
e
d
ata
b
ase,
ca
lcu
lates
th
e
E
u
clid
ea
n
d
is
tan
ce
f
o
r
ea
c
h
wo
r
d
,
an
d
class
if
ies th
e
d
ata
i
n
to
o
n
e
o
f
th
e
lab
els (
r
ed
,
y
ell
o
w,
g
r
ee
n
,
o
r
wh
ite
)
.
T
h
e
r
esu
lts
ar
e
v
is
u
alize
d
,
as
s
h
o
wn
in
Fig
u
r
e
3
.
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A
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r
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An
al
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g
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lt
T
h
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ter
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ter
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r
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e
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t
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ed
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h
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en
d
is
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lay
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tab
le
o
f
im
p
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f
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o
m
th
e
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t
m
in
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g
p
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ce
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s
.
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n
th
is
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y
s
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te
s
tin
g
,
a
s
am
p
le
o
f
d
ata
was
tak
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d
o
m
l
y
f
r
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m
th
e
d
atab
ase,
co
n
s
titu
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1
0
%
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f
th
e
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ataset.
T
h
e
s
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n
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t
was
th
en
en
ter
ed
in
to
th
e
n
ews
in
p
u
t
f
o
r
m
,
r
esu
ltin
g
in
th
e
f
o
llo
win
g
o
u
tc
o
m
es:
T
ab
le
3
s
h
o
ws
th
e
r
esu
lts
o
f
th
e
q
u
er
y
test
in
g
ex
p
er
im
en
t
co
n
d
u
cted
o
n
th
e
s
y
s
tem
.
T
en
n
ews
ar
ticles
wer
e
r
an
d
o
m
l
y
s
elec
ted
f
r
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m
th
e
c
o
n
ten
t
d
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ase
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d
th
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n
in
p
u
t
in
to
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e
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y
s
tem
u
s
in
g
th
e
n
ews
in
p
u
t f
o
r
m
an
d
Fig
u
r
e
4
s
h
o
w
th
e
ex
tr
ac
tio
n
c
o
n
ten
t f
r
o
m
t
h
e
web
s
ite
d
a
’
wah
.
T
ab
le
3
.
R
esu
lt o
f
q
u
er
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in
g
ex
p
er
i
m
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n
t
No
Te
st
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e
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t
La
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e
l
R
e
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h
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h
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h
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Fig
u
r
e
4
.
E
x
tr
ac
tio
n
c
o
n
ten
t r
e
s
u
lt
T
h
is
ap
p
licatio
n
m
ea
s
u
r
es
th
e
alg
o
r
ith
m
’
s
ac
cu
r
ac
y
in
co
r
r
e
ctly
class
if
y
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g
d
o
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m
e
n
ts
in
to
th
e
f
o
u
r
s
p
ec
if
ied
ca
teg
o
r
ies.
T
h
e
ac
cu
r
ac
y
ca
lcu
latio
n
is
d
etailed
b
elo
w.
(
%
)
=
∑
∑
*
1
0
0
(
1
)
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14
,
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2
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u
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s
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20
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:
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582
B
ased
o
n
th
e
eq
u
atio
n
,
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h
e
ac
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r
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y
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h
iev
ed
is
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9
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0
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%.
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h
is
was
test
ed
u
s
in
g
cr
o
s
s
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atio
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er
if
y
th
e
co
r
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ess
o
f
th
e
m
an
u
al
ca
lcu
latio
n
s
.
T
h
e
clas
s
if
icatio
n
r
esu
lts
wer
e
th
en
an
aly
ze
d
to
d
eter
m
in
e
th
e
ac
cu
r
ac
y
u
s
in
g
th
e
co
n
f
u
s
io
n
m
atr
i
x
.
T
h
e
c
o
n
f
u
s
io
n
m
a
tr
ix
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lcu
latio
n
f
o
c
u
s
es
o
n
tr
u
e
p
o
s
itiv
e
item
s
o
r
v
ar
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les,
u
tili
zin
g
th
e
(
2
)
.
(
)
=
+
(
2
)
=
+
+
+
+
=
+
T
h
e
test
r
esu
lts
h
elp
d
eter
m
i
n
e
th
e
o
p
tim
al
k
v
alu
e
f
o
r
m
ax
im
u
m
s
u
cc
ess
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n
t
h
is
s
tu
d
y
,
k
v
alu
es
f
r
o
m
1
to
3
0
wer
e
test
ed
.
Ho
wev
er
,
n
o
t
all
k
v
al
u
es
y
ield
ed
s
ig
n
if
ican
t
r
esu
lts
,
s
o
o
n
ly
th
e
m
o
s
t
ef
f
ec
tiv
e
k
v
alu
es
wer
e
s
elec
ted
,
it
is
ev
id
en
t
th
at
th
e
o
p
tim
al
a
n
d
s
tab
le
k
v
alu
e
is
ac
h
iev
e
d
at
k
=
7
an
d
b
e
y
o
n
d
,
in
d
icatin
g
th
at
k
=
7
p
r
o
v
i
d
es
th
e
b
est
ac
cu
r
ac
y
.
T
h
e
g
r
ap
h
b
elo
w
i
n
F
ig
u
r
e
5
illu
s
tr
ates
th
e
o
p
tim
al
k
v
alu
e
id
en
tifie
d
in
th
is
r
esear
ch
.
Fig
u
r
e
5
.
R
ad
ical
k
-
o
p
tim
al
T
h
e
r
esu
lt
s
h
o
ws
th
at
th
e
o
p
t
im
al
r
esu
lt
is
o
b
tain
ed
with
a
k
v
al
u
e
o
f
6
.
T
h
is
is
d
u
e
to
th
e
lar
g
e
s
p
r
ea
d
o
f
d
is
tan
ce
v
alu
es
b
et
wee
n
d
if
f
er
e
n
t
class
es.
T
h
e
n
u
m
b
er
o
f
k
d
eter
m
in
es
h
o
w
m
an
y
d
ata
p
o
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ts
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av
e
th
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s
est
d
is
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ce
,
w
h
ich
is
th
en
u
s
ed
to
ca
lcu
late
t
h
e
m
o
d
e
f
o
r
p
r
ed
ictin
g
th
e
m
o
s
t
co
m
m
o
n
class
if
icatio
n
class
.
Af
ter
d
et
er
m
in
in
g
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
class
if
icatio
n
,
we
th
en
m
ea
s
u
r
e
th
e
p
r
ec
is
io
n
an
d
r
ec
all
v
alu
es
f
o
r
ea
c
h
class
to
u
n
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e
r
s
tan
d
th
e
clo
s
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ess
o
f
th
e
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elatio
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s
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ip
s
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etwe
en
th
e
clas
s
es.
B
elo
w
ar
e
th
e
p
r
ec
is
io
n
r
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lts
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o
r
ea
c
h
class
s
h
o
w
in
T
ab
le
4
.
T
ab
le
4
.
Me
asu
r
em
e
n
t th
e
p
r
e
cisi
o
n
class
if
icatio
n
C
l
a
s
s
K
1
2
3
4
5
6
R
e
d
0
.
1
3
3
0
.
2
1
4
0
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1
4
3
0
.
1
4
3
0
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2
3
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0
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4
5
7
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4
5
7
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3
8
5
0
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5
3
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5
8
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4
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5
3
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5
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e
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n
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.
0
8
9
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0
7
8
0
.
0
8
9
0
.
1
2
8
0
.
1
7
8
0
.
2
1
0
0
.
2
1
0
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h
i
t
e
0
.
6
3
2
0
.
7
0
1
0
.
6
9
0
0
.
6
9
0
0
.
6
3
2
0
.
7
4
1
0
.
7
4
1
W
h
en
co
m
p
ar
e
d
to
th
e
v
al
u
e
s
in
th
e
tab
les
ab
o
v
e,
it
ca
n
b
e
s
ee
n
th
at
th
e
“
W
h
ite
”
class
h
as
th
e
f
o
llo
win
g
p
r
ec
is
io
n
v
alu
es:
k
1
=
0
.
6
8
9
,
k
2
=
0
.
8
2
4
,
k
3
=
0
.
7
9
7
,
k
4
=
0
.
7
8
4
,
k
5
=
0
.
6
8
3
,
k
6
=
0
.
8
1
1
,
an
d
k
7
=
0
.
8
1
1
,
with
an
av
er
a
g
e
in
cr
e
ase
o
f
0
.
7
7
1
.
T
h
e
h
ig
h
est
v
alu
e
is
o
b
tain
ed
at
k
2
,
co
m
p
a
r
ed
to
all
class
es.
T
h
e
“
W
h
ite
”
class
h
as th
e
h
ig
h
est p
r
ec
is
io
n
an
d
r
ec
all
v
alu
e
s
ac
r
o
s
s
all
k
v
alu
es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
I
SS
N:
2252
-
8
7
7
6
A
n
a
lyzi
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g
r
a
d
ica
lis
m
s
en
timen
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o
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ite
d
a
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A
u
lia
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iz
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)
583
4.
CO
NCLU
SI
O
N
T
h
is
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tu
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y
d
e
m
o
n
s
tr
ates
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e
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ess
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te
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m
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if
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g
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ical
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ten
t
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n
d
o
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esian
Da
’
wah
o
n
web
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s
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g
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ased
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ch
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g
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ce
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m
p
ar
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with
k
e
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wo
r
d
s
s
to
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ed
in
a
d
atab
ase,
u
s
in
g
1
2
6
lab
eled
a
r
ticles
f
r
o
m
th
e
Min
is
tr
y
o
f
C
o
m
m
u
n
icatio
n
an
d
I
n
f
o
r
m
ati
cs.
T
h
e
K
-
NN
alg
o
r
ith
m
,
with
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o
p
tim
al
k
o
f
7
,
ac
h
iev
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d
a
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%
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r
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ate.
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h
e
r
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lts
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ig
h
lig
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ted
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“
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h
ite
”
class
’
s
h
ig
h
p
r
e
cisi
o
n
an
d
r
ec
all.
Per
f
o
r
m
a
n
c
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test
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g
s
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tim
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o
f
0
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4
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e
co
n
d
s
an
d
m
em
o
r
y
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s
ag
e
o
f
8
8
4
,
6
5
6
b
y
tes,
in
d
icatin
g
ef
f
ici
en
cy
with
r
o
o
m
f
o
r
im
p
r
o
v
em
e
n
t.
Fu
tu
r
e
en
h
an
ce
m
en
ts
in
clu
d
e
ad
d
in
g
s
y
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id
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th
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o
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ith
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x
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latf
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lin
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M
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S
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h
e
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th
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r
s
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ar
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m
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n
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m
atics
o
f
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th
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lim
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th
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h
eir
c
o
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tio
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s
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av
e
s
ig
n
if
ican
tly
en
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ich
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h
e
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d
th
eir
s
u
p
p
o
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t is g
r
e
atly
ap
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ec
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.
F
UNDING
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NF
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esear
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u
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elig
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R
esear
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Gr
an
t Sch
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e
w
ith
Pro
p
o
s
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Nu
m
b
e
r
Deta
il 2
2
1
1
8
0
0
0
0
0
5
8
5
9
1
.
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
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M
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N
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Na
m
e
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So
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R
is
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ah
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J
u
air
iah
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Mu
n
s
y
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✓
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✓
✓
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C
:
C
o
n
c
e
p
t
u
a
l
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z
a
t
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n
M
:
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lict o
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t
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est.
I
NF
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e
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e
o
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tain
ed
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r
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m
all
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h
e
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elate
d
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m
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n
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e
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as
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d
with
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th
e
r
elev
an
t
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atio
n
al
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eg
u
l
atio
n
s
an
d
in
s
titu
tio
n
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o
licies
in
ac
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r
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with
th
e
te
n
ets
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f
t
h
e
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ls
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Dec
lar
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n
an
d
h
as
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ee
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ap
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e
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y
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e
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th
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r
s
'
in
s
titu
tio
n
al
r
ev
iew
b
o
ar
d
o
r
eq
u
i
v
alen
t c
o
m
m
ittee.
DATA AV
A
I
L
AB
I
L
I
T
Y
T
h
e
d
ata
th
at
s
u
p
p
o
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o
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d
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e
av
aila
b
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o
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est
f
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o
m
th
e
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n
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g
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th
o
r
,
Mu
n
s
y
i.
T
h
e
d
ata,
wh
ich
co
n
tain
in
f
o
r
m
atio
n
t
h
at
co
u
ld
co
m
p
r
o
m
is
e
th
e
p
r
iv
ac
y
o
f
r
esear
ch
p
ar
ticip
an
ts
,
ar
e
n
o
t p
u
b
licly
a
v
ailab
le
d
u
e
to
ce
r
tain
r
estrictio
n
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
7
6
I
n
t J
I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
,
Vo
l.
14
,
No
.
2
,
A
u
g
u
s
t
20
25
:
575
-
585
584
RE
F
E
R
E
NC
E
S
[
1
]
Y
.
El
o
v
i
c
i
e
t
a
l
.
,
“
C
o
n
t
e
n
t
-
b
a
s
e
d
d
e
t
e
c
t
i
o
n
o
f
t
e
r
r
o
r
i
st
s
b
r
o
w
si
n
g
t
h
e
w
e
b
u
s
i
n
g
a
n
a
d
v
a
n
c
e
d
t
e
r
r
o
r
d
e
t
e
c
t
i
o
n
s
y
st
e
m
(
A
TD
S
)
,
”
L
e
c
t
u
re
N
o
t
e
s
i
n
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
v
o
l
.
3
4
9
5
,
p
p
.
2
4
4
–
2
5
5
,
2
0
0
5
,
d
o
i
:
1
0
.
1
0
0
7
/
1
1
4
2
7
9
9
5
_
2
0
.
[
2
]
Y
.
R
a
h
m
a
t
u
l
l
a
h
,
“
R
a
d
i
c
a
l
i
sm,
j
i
h
a
d
a
n
d
t
e
r
r
o
r
,
”
Al
-
A
l
b
a
b
,
v
o
l
.
6
,
n
o
.
2
,
p
p
.
1
5
1
–
1
6
6
,
2
0
1
7
.
[
3
]
M
.
F
u
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.
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