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ro
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m
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
5
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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.
3
6
,
No
.
3
,
Dec
em
b
er
20
24
:
1
9
1
9
-
1
9
2
8
1920
th
er
ef
o
r
e
r
ec
o
m
m
e
n
d
item
s
o
r
s
er
v
ices
ad
ap
ted
to
s
u
ch
p
r
e
f
er
en
ce
s
lear
n
ed
f
r
o
m
p
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ch
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ices.
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n
th
e
co
n
tex
t
o
f
to
u
r
is
m
,
r
ec
o
m
m
en
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m
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n
d
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s
cu
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d
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r
av
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-
r
elate
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s
er
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[
1
]
,
[
2
]
.
C
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llab
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r
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f
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in
g
(
C
F)
ap
p
r
o
ac
h
es,
wh
ile
wid
ely
ad
o
p
ted
in
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m
m
en
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er
s
y
s
tem
s
,
s
tr
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g
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le
to
y
ield
s
atis
f
y
in
g
to
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r
is
m
r
ec
o
m
m
en
d
atio
n
s
d
u
e
to
th
eir
lim
ita
tio
n
s
.
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y
,
th
eir
u
s
e
o
f
s
in
g
le
-
cr
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io
n
r
atin
g
s
m
ak
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it
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if
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icu
lt
to
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e
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lect
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ately
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en
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h
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f
o
r
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ce
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is
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m
p
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is
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o
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v
ar
io
u
s
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ts
s
u
ch
as
lo
ca
tio
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en
ities
,
q
u
ality
o
f
s
er
v
ice,
a
n
d
o
v
e
r
all
am
b
ian
ce
ea
ch
wit
h
g
r
ea
ter
o
r
less
er
im
p
o
r
tan
ce
to
d
if
f
er
e
n
t
tr
av
e
ler
s
[
3
]
.
Seco
n
d
l
y
,
C
F
-
b
ased
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ec
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m
m
en
d
er
s
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ata
s
p
ar
s
ity
,
p
ar
ticu
lar
ly
wh
en
r
e
co
m
m
en
d
i
n
g
to
u
s
er
s
wh
er
e
th
er
e
is
v
er
y
l
ittle
o
r
n
o
u
s
er
-
item
in
ter
ac
tio
n
al
h
is
to
r
y
av
ailab
le.
T
h
is
s
p
ar
s
ity
ch
allen
g
e
lead
s
to
lo
wer
ac
cu
r
ac
y
o
f
p
r
ed
ictio
n
s
an
d
th
er
ef
o
r
e,
less
p
er
s
o
n
aliza
tio
n
in
t
h
e
r
ec
o
m
m
en
d
atio
n
s
[
4
]
.
T
o
o
v
er
c
o
m
e
th
ese
lim
itatio
n
s
,
a
m
o
r
e
r
o
b
u
s
t
ap
p
r
o
ac
h
th
at
tak
es
in
to
ac
co
u
n
t
b
o
th
th
e
m
u
lti
-
d
im
en
s
io
n
al
asp
ec
t
o
f
in
d
iv
id
u
al
p
r
ef
er
en
c
es
an
d
co
m
p
lem
en
tar
y
s
o
u
r
ce
s
o
f
in
f
o
r
m
atio
n
m
ig
h
t
b
e
n
ee
d
e
d
.
R
ec
en
t
r
esear
ch
h
as
ex
p
l
o
r
ed
two
p
r
o
m
is
in
g
s
tr
ea
m
s
:
m
u
l
ti
-
cr
iter
ia
(
MC)
r
ec
o
m
m
e
n
d
e
r
s
y
s
tem
s
an
d
th
e
in
teg
r
atio
n
o
f
s
o
cial
tr
u
s
t
n
etwo
r
k
s
.
MC
r
ec
o
m
m
en
d
er
s
y
s
tem
s
ex
ten
d
b
ey
o
n
d
s
in
g
le
r
atin
g
s
b
y
in
co
r
p
o
r
atin
g
u
s
er
f
ee
d
b
ac
k
o
n
s
p
ec
if
ic
att
r
ib
u
tes
o
f
item
s
.
B
y
tak
i
n
g
t
h
ese
f
in
e
-
g
r
ain
ed
p
r
e
f
er
en
ce
s
in
to
ac
c
o
u
n
t,
s
u
ch
s
y
s
tem
s
ca
n
m
ak
e
r
ec
o
m
m
en
d
atio
n
s
th
at
ar
e
clo
s
er
to
th
e
ac
t
u
al
u
s
er
p
r
io
r
ities
[
5
]
-
[
7
]
.
Alo
n
g
s
id
e,
s
o
cial
tr
u
s
t
n
etwo
r
k
s
h
av
e
b
ee
n
ex
p
lo
r
ed
to
ad
d
r
ess
d
ata
s
p
ar
s
en
ess
.
I
n
ad
d
itio
n
to
d
is
co
v
er
in
g
laten
t
u
s
er
p
r
ef
er
e
n
ce
s
th
r
o
u
g
h
s
o
cial
in
ter
ac
tio
n
s
,
th
ese
n
etwo
r
k
s
ex
p
o
s
e
tr
u
s
t
r
el
atio
n
s
h
ip
s
b
etwe
en
u
s
er
s
an
d
item
s
th
at
s
u
n
lig
h
t
p
o
ten
tial
ly
in
f
lu
en
ce
s
co
n
f
ig
u
r
atio
n
s
.
Ho
wev
er
,
th
e
ex
p
licit
tr
u
s
t
r
elatio
n
s
h
ip
s
with
in
th
es
e
n
etwo
r
k
s
ca
n
also
b
e
s
p
ar
s
e,
r
eq
u
i
r
in
g
th
e
r
ef
lect
io
n
o
f
im
p
licit c
o
n
n
ec
tio
n
s
d
er
iv
ed
f
r
o
m
u
s
er
-
item
in
te
r
ac
tio
n
s
[
8
]
.
R
ec
en
tly
,
r
ec
o
m
m
e
n
d
er
s
y
s
tem
s
h
av
e
b
ec
o
m
e
in
d
is
p
en
s
ab
le
in
th
e
to
u
r
is
m
d
o
m
ai
n
b
y
allev
iatin
g
in
f
o
r
m
atio
n
o
v
er
l
o
ad
an
d
p
r
o
v
id
in
g
p
er
s
o
n
alize
d
r
ec
o
m
m
en
d
atio
n
s
to
tr
av
eler
s
.
R
esear
ch
er
s
h
av
e
wid
ely
ex
p
lo
r
ed
v
ar
io
u
s
ap
p
r
o
ac
h
es
to
en
h
a
n
ce
th
e
p
e
r
f
o
r
m
an
c
e
o
f
th
ese
s
y
s
tem
s
,
p
ar
ticu
l
ar
ly
f
o
r
h
o
tel
an
d
r
estau
r
an
t
r
ec
o
m
m
e
n
d
atio
n
s
.
I
n
th
e
h
o
tel
d
o
m
ain
,
r
ec
o
m
m
en
d
er
s
y
s
tem
s
ar
e
cr
u
cial
f
o
r
tr
av
eler
s
wh
o
n
ee
d
ass
is
tan
ce
in
p
ick
in
g
ac
co
m
m
o
d
atio
n
s
th
at
s
u
it
th
em
b
est.
Fo
r
o
u
za
n
d
eh
et
a
l.
[
9
]
p
r
o
p
o
s
ed
a
n
o
v
el
ap
p
r
o
ac
h
co
m
b
in
in
g
th
e
ar
tific
ial
b
ee
co
lo
n
y
alg
o
r
ith
m
a
n
d
th
e
f
u
zz
y
T
OPSIS
m
o
d
el,
lev
er
ag
in
g
d
ata
f
r
o
m
T
r
ip
Ad
v
is
o
r
f
o
r
tu
n
i
n
g
h
o
tel
r
ec
o
m
m
en
d
atio
n
s
d
e
p
en
d
i
n
g
o
n
u
s
er
s
p
ec
if
icatio
n
s
.
Simila
r
ly
,
C
u
i
et
a
l.
[
1
0
]
d
ev
elo
p
e
d
a
h
o
tel
r
ec
o
m
m
en
d
atio
n
alg
o
r
ith
m
th
at
u
tili
ze
s
o
n
lin
e
r
ev
iews a
n
d
p
r
o
b
ab
ilis
tic
lin
g
u
is
tic
ter
m
s
ets
(
PLT
S).
User
s
o
f
ten
ex
p
r
ess
th
eir
s
en
tim
en
ts
with
a
g
r
ea
t
d
ea
l
o
f
am
b
ig
u
ity
an
d
u
n
ce
r
t
ain
ty
in
th
e
r
ev
iew
tex
t,
wh
ich
m
ak
es
it
d
if
f
icu
l
t
f
o
r
an
au
to
m
atic
s
y
s
tem
to
ca
p
tu
r
e
all
s
u
ch
ex
p
r
ess
io
n
s
;
th
er
ef
o
r
e,
th
eir
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
tr
an
s
lates
u
s
er
s
en
tim
en
t
ex
p
r
ess
ed
th
r
o
u
g
h
n
atu
r
al
lan
g
u
a
g
e
in
t
o
PL
T
Ss
th
at
r
ep
r
esen
t
m
o
r
e
ac
c
u
r
ate
as
well
as
r
e
f
lectiv
e
r
ec
o
m
m
en
d
atio
n
s
.
Xia
et
a
l.
[
1
1
]
i
n
tr
o
d
u
ce
d
a
d
ee
p
n
e
u
r
al
n
etwo
r
k
m
o
d
e
l
th
at
co
m
b
i
n
es
p
ictu
r
es,
tex
t,
an
d
s
co
r
i
n
g
d
ata
f
r
o
m
u
s
er
r
ev
iews
to
p
r
o
v
id
e
h
o
lis
tic
r
ec
o
m
m
en
d
atio
n
s
f
o
r
h
o
tels
.
T
o
im
p
r
o
v
e
r
ec
o
m
m
e
n
d
atio
n
ac
cu
r
ac
y
,
J
o
s
e
et
a
l.
[
1
2
]
p
r
o
p
o
s
ed
a
h
y
b
r
id
a
p
p
r
o
ac
h
b
ased
o
n
d
ilated
m
u
ltich
an
n
el
co
n
v
o
lu
tio
n
al
n
e
u
r
al
n
etwo
r
k
s
(
C
NN)
an
d
b
id
i
r
ec
tio
n
al
g
ated
r
ec
u
r
r
en
t
u
n
its
(
B
iGR
U)
with
an
atten
tio
n
m
ec
h
an
is
m
th
at
ca
n
ca
p
tu
r
e
lo
n
g
-
ter
m
s
em
a
n
tic
ch
ar
ac
ter
is
tics
.
R
eg
ar
d
in
g
r
estau
r
an
t
r
ec
o
m
m
en
d
atio
n
s
,
r
ec
o
m
m
en
d
e
r
s
y
s
tem
s
p
lay
a
cr
u
cial
r
o
le
in
s
tr
ea
m
lin
in
g
th
e
d
in
in
g
e
x
p
er
ie
n
ce
f
o
r
u
s
er
s
.
Asan
i
et
a
l.
[
1
3
]
in
tr
o
d
u
ce
d
a
co
m
m
en
t
-
b
ased
c
o
n
tex
t
-
aw
ar
e
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
th
at
ex
tr
ac
ted
f
o
o
d
p
r
ef
er
en
ce
s
f
r
o
m
u
s
er
co
m
m
en
ts
an
d
r
ec
o
m
m
en
d
e
d
r
e
s
tau
r
an
ts
with
h
ig
h
p
r
ec
is
io
n
in
th
eir
e
v
alu
atio
n
s
.
Dee
p
lear
n
in
g
tech
n
iq
u
es
h
av
e
also
b
ee
n
em
p
lo
y
ed
in
r
estau
r
an
t
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
s
.
Sae
lim
an
d
Kijs
ir
ik
u
l
[
1
4
]
d
ev
elo
p
ed
a
d
ee
p
n
eu
r
al
n
etwo
r
k
m
o
d
el
f
o
r
r
estau
r
an
t
r
ec
o
m
m
en
d
atio
n
s
in
T
h
ailan
d
.
T
h
is
m
o
d
el
in
teg
r
ates
d
if
f
er
e
n
t
f
ea
tu
r
es
s
u
ch
as
u
s
er
p
r
ef
er
en
ce
s
,
lo
ca
tio
n
,
an
d
d
in
in
g
h
is
to
r
y
to
p
r
o
v
i
d
e
m
o
r
e
p
er
s
o
n
alize
d
d
in
in
g
r
ec
o
m
m
en
d
atio
n
s
,
th
u
s
en
h
a
n
cin
g
th
e
o
v
er
all
u
s
er
ex
p
er
ien
ce
.
On
th
e
o
th
er
h
an
d
,
Yan
g
et
a
l.
[
1
5
]
d
ev
elo
p
ed
a
p
er
s
o
n
alize
d
r
estau
r
an
t
r
ec
o
m
m
en
d
atio
n
m
o
d
el
u
s
in
g
d
ee
p
lear
n
in
g
an
d
b
ig
d
ata.
T
h
eir
m
o
d
el
u
tili
ze
s
b
r
o
ad
d
atasets
to
r
ec
o
g
n
ize
c
u
s
to
m
er
b
e
h
av
io
r
an
d
p
r
ef
er
en
ce
s
,
m
ak
in
g
it
p
o
s
s
ib
le
to
o
f
f
e
r
p
er
s
o
n
alize
d
r
ec
o
m
m
en
d
atio
n
s
th
at
af
f
ec
t
cu
s
to
m
er
d
ec
is
io
n
-
m
ak
i
n
g
.
Per
u
m
al
et
a
l.
[
1
6
]
tack
led
th
e
co
ld
-
s
tar
t
p
r
o
b
lem
in
r
est
au
r
an
t
r
ec
o
m
m
e
n
d
er
s
y
s
tem
s
u
s
in
g
an
o
n
to
lo
g
y
-
b
ased
ap
p
r
o
ac
h
.
On
to
lo
g
ies
c
an
b
e
u
s
ed
t
o
m
o
d
el
th
e
h
ier
a
r
ch
y
o
f
r
elatio
n
s
(
e.
g
.
,
b
etwe
e
n
d
if
f
e
r
en
t
t
y
p
es
o
f
cu
is
in
es,
r
estau
r
an
t p
r
o
p
er
ties
,
an
d
u
s
er
p
r
ef
er
en
ce
s
)
en
a
b
lin
g
th
e
s
y
s
tem
to
m
ak
e
in
f
o
r
m
ed
r
ec
o
m
m
en
d
atio
n
s
ev
en
wh
en
lim
ited
d
ata
is
av
ai
lab
le.
Dr
awin
g
in
s
p
ir
atio
n
f
r
o
m
t
h
e
ab
o
v
e
-
m
e
n
tio
n
ed
ad
v
a
n
ce
m
en
ts
an
d
th
e
s
u
cc
ess
ac
h
iev
ed
in
th
e
u
s
e
o
f
h
y
b
r
id
m
eth
o
d
o
lo
g
ies
in
r
ec
o
m
m
en
d
er
s
y
s
tem
s
,
th
is
s
tu
d
y
p
r
o
p
o
s
es
a
h
y
b
r
id
m
u
lti
-
cr
it
er
ia
tr
u
s
t
-
en
h
an
ce
d
co
llab
o
r
ativ
e
f
ilter
in
g
(
HM
C
T
eCF
)
alg
o
r
ith
m
f
o
r
p
e
r
s
o
n
alize
d
to
u
r
is
m
r
ec
o
m
m
e
n
d
at
io
n
s
.
T
h
e
g
o
al
o
f
HM
C
T
eC
F
is
to
s
u
r
p
ass
th
e
li
m
itatio
n
s
o
f
tr
ad
itio
n
al
r
ec
o
m
m
en
d
er
s
y
s
tem
s
b
y
in
teg
r
atin
g
m
u
lti
-
cr
iter
ia
u
s
er
p
r
ef
er
en
ce
s
with
tr
u
s
t
r
elatio
n
s
h
ip
s
b
etwe
en
u
s
er
s
an
d
ite
m
s
.
T
h
is
s
y
n
th
esis
is
p
r
o
p
o
s
ed
to
b
o
o
s
t
b
o
th
th
e
ac
cu
r
ac
y
an
d
co
v
er
ag
e
o
f
r
ec
o
m
m
en
d
atio
n
s
,
e
v
en
tu
ally
s
atis
f
y
in
g
tr
a
v
el
s
elec
tio
n
s
.
T
h
e
p
r
o
p
o
s
ed
HM
C
T
eCF
alg
o
r
ith
m
b
u
ild
s
o
n
p
r
e
v
io
u
s
r
es
ea
r
ch
in
to
u
r
is
m
r
ec
o
m
m
en
d
e
r
s
y
s
tem
s
b
y
in
teg
r
ati
n
g
m
u
lti
-
cr
iter
ia
a
p
p
r
o
ac
h
es
with
tr
u
s
t
n
etwo
r
k
s
.
E
ar
lier
s
tu
d
ies,
s
u
ch
as
[
9
]
,
[
1
5
]
,
f
o
cu
s
ed
o
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
A
mu
lti
-
crit
eria
tr
u
s
t
-
en
h
a
n
ce
d
co
lla
b
o
r
a
tive
filt
erin
g
a
lg
o
r
ith
m
…
(
Qu
s
a
i Y.
S
h
a
m
b
o
u
r
)
1921
s
p
ec
if
ic
tech
n
iq
u
es
s
u
ch
as
a
r
tific
ial
in
tellig
en
ce
o
r
d
ee
p
l
ea
r
n
in
g
.
I
n
co
n
tr
ast,
th
is
s
tu
d
y
co
m
b
in
es
m
u
lti
-
cr
iter
ia
p
r
ef
er
en
ce
s
an
d
tr
u
s
t
r
elatio
n
s
h
ip
s
to
ad
d
r
ess
th
e
lim
itatio
n
s
o
f
tr
ad
itio
n
al
C
F.
B
y
m
er
g
in
g
th
ese
ad
v
an
ce
d
ap
p
r
o
ac
h
es,
th
e
HM
C
T
eC
F
alg
o
r
ith
m
aim
s
to
p
r
o
v
id
e
m
o
r
e
ac
c
u
r
ate
an
d
p
er
s
o
n
alize
d
r
ec
o
m
m
en
d
atio
n
s
in
to
u
r
is
m
.
I
t
ef
f
ec
tiv
ely
tack
les
ch
allen
g
es
lik
e
d
ata
s
p
ar
s
ity
th
at
h
av
e
h
in
d
er
e
d
ea
r
lier
s
y
s
tem
s
.
T
h
e
p
r
o
p
o
s
ed
HM
C
T
eCF
alg
o
r
ith
m
in
clu
d
es
th
r
ee
in
te
r
r
ela
ted
m
o
d
u
les:
a
u
s
er
-
b
ased
m
u
lti
-
cr
iter
ia
tr
u
s
t
-
en
h
an
ce
d
C
F,
an
ite
m
-
b
ased
m
u
lti
-
cr
iter
ia
tr
u
s
t
-
en
h
an
ce
d
C
F,
an
d
a
h
y
b
r
i
d
r
ec
o
m
m
en
d
atio
n
m
ec
h
an
is
m
.
T
h
r
o
u
g
h
d
ir
ec
t,
p
r
o
p
a
g
ated
,
an
d
o
v
er
all
tr
u
s
t
s
co
r
es
to
g
eth
er
with
m
u
lti
-
cr
iter
ia
r
atin
g
s
,
th
e
HM
C
T
eC
F
is
d
esig
n
ed
to
p
r
o
v
id
e
p
er
s
o
n
alize
d
y
et
d
iv
er
s
e
r
ec
o
m
m
en
d
ati
o
n
s
d
ed
icate
d
to
cu
m
u
lativ
e
u
s
er
in
tellig
en
ce
.
T
h
r
o
u
g
h
ex
te
n
s
iv
e
ex
p
er
im
en
ts
o
n
r
ea
l
-
wo
r
ld
d
atasets
f
r
o
m
T
r
ip
Ad
v
is
o
r
,
in
clu
d
in
g
b
o
th
r
estau
r
an
t
an
d
h
o
tel
r
atin
g
s
,
we
ev
alu
ate
th
e
ef
f
ec
tiv
en
ess
o
f
th
e
HM
C
T
eC
F
alg
o
r
ith
m
f
o
r
r
estau
r
an
t
an
d
h
o
tel
r
atin
g
p
r
ed
ictio
n
s
.
Ad
d
itio
n
ally
,
we
test
th
e
alg
o
r
ith
m
’
s
p
er
f
o
r
m
an
ce
u
n
d
e
r
d
if
f
er
en
t
d
ata
s
p
ar
s
ity
s
ce
n
ar
io
s
.
Ou
r
r
esu
lts
d
em
o
n
s
tr
ate
th
at
th
e
HM
C
T
eC
F
alg
o
r
ith
m
co
n
s
is
ten
tly
o
u
tp
e
r
f
o
r
m
s
b
en
c
h
m
ar
k
m
eth
o
d
s
in
ter
m
s
o
f
p
r
ed
icti
o
n
ac
cu
r
ac
y
a
n
d
r
ec
o
m
m
en
d
atio
n
co
v
er
ag
e
.
Par
ticu
lar
ly
,
it
ac
h
iev
es
g
r
ea
ter
p
r
ed
ictio
n
ac
cu
r
ac
y
,
d
em
o
n
s
tr
atin
g
a
clo
s
er
alig
n
m
en
t
b
etwe
en
r
ec
o
m
m
en
d
atio
n
s
an
d
ac
tu
al
u
s
er
p
r
ef
er
en
ce
s
.
Fu
r
th
er
m
o
r
e,
th
e
alg
o
r
ith
m
s
h
o
ws
a
n
o
tab
le
c
o
v
er
ag
e
r
ate,
s
h
o
wca
s
in
g
its
ab
ilit
y
to
r
ec
o
m
m
en
d
a
d
iv
er
s
e
s
et
o
f
to
u
r
is
m
-
r
elate
d
f
ac
ilit
ies.
2.
ARCH
I
T
E
C
T
URA
L
O
VE
R
VIE
W
O
F
T
H
E
H
M
C
T
eCF
AL
G
O
RI
T
H
M
T
h
is
s
tu
d
y
in
tr
o
d
u
ce
s
an
ef
f
ec
tiv
e
HM
C
T
eCF
alg
o
r
it
h
m
d
esig
n
ed
s
p
ec
if
ically
f
o
r
to
u
r
is
m
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
s
.
T
h
e
alg
o
r
ith
m
co
m
p
r
is
es
th
r
ee
p
r
im
ar
y
m
o
d
u
les:
th
e
u
s
er
-
b
ased
m
u
lti
-
cr
iter
ia
tr
u
s
t
-
en
h
an
ce
d
co
llab
o
r
ativ
e
f
ilter
in
g
m
o
d
u
le,
th
e
item
-
b
ased
m
u
lti
-
cr
iter
ia
tr
u
s
t
-
en
h
a
n
ce
d
co
llab
o
r
ativ
e
f
ilter
in
g
m
o
d
u
le,
an
d
th
e
h
y
b
r
id
r
ec
o
m
m
en
d
atio
n
m
o
d
u
le.
T
h
ese
m
o
d
u
les
wo
r
k
in
s
y
n
er
g
y
to
p
r
o
v
id
e
m
o
r
e
ac
cu
r
ate
an
d
p
er
s
o
n
alize
d
to
u
r
is
m
-
r
elate
d
r
ec
o
m
m
e
n
d
atio
n
s
.
2
.
1
.
T
he
us
er
-
ba
s
ed
m
ulti
-
cr
it
er
ia
t
rus
t
-
enha
nced
CF
m
o
du
le
T
h
is
m
o
d
u
le
h
a
r
n
ess
es
th
e
p
o
wer
o
f
tr
u
s
t
r
elatio
n
s
h
ip
s
am
o
n
g
u
s
er
s
an
d
m
u
lti
-
cr
iter
ia
r
atin
g
s
to
p
r
o
d
u
ce
u
s
er
-
b
ased
tr
u
s
t
-
en
h
a
n
ce
d
p
r
ed
ictio
n
s
b
y
ca
lcu
latin
g
d
ir
ec
t,
p
r
o
p
a
g
ated
,
an
d
o
v
er
all
tr
u
s
t
s
co
r
es.
T
h
e
p
r
o
ce
s
s
u
n
f
o
l
d
s
in
s
ev
er
al
s
tep
s
:
Step
1
:
a
s
s
ig
n
tr
u
s
t v
alu
es f
o
r
u
s
er
s
b
ased
o
n
th
eir
in
ter
ac
tio
n
s
T
r
u
s
two
r
th
in
ess
b
etwe
en
u
s
er
s
is
ass
es
s
ed
b
ased
o
n
t
h
eir
r
eliab
ilit
y
i
n
p
r
o
v
id
i
n
g
ac
cu
r
ate
r
ec
o
m
m
en
d
atio
n
s
,
wh
ich
co
r
r
elate
s
with
u
s
er
s
im
ilar
ity
[
1
7
]
.
T
o
in
itiate
th
e
p
r
e
d
ictio
n
p
r
o
ce
s
s
,
we
f
ir
s
t
em
p
lo
y
th
e
f
o
llo
win
g
f
o
r
m
u
la
to
ca
lcu
late
th
e
p
r
e
d
icted
r
atin
g
s
f
o
r
ea
ch
u
s
er
p
air
,
as
(
1
)
.
,
=
̄
+
(
(
)
−
̄
)
(
1
)
I
n
th
is
f
o
r
m
u
la,
̄
an
d
̄
d
en
o
te
th
e
av
er
ag
e
r
atin
g
s
p
r
o
v
i
d
ed
b
y
u
s
er
s
x
an
d
y
,
r
esp
ec
tiv
ely
.
(
)
r
ep
r
esen
ts
u
s
er
y
’
s
o
v
er
all
u
tili
ty
f
o
r
item
i
.
T
h
is
u
tili
ty
s
co
r
e
is
d
ef
in
ed
as
(
2
)
.
(
)
=
∑
(
)
×
(
=
1
)
,
ℎ
∑
(
)
=
1
=
1
(
2
)
W
ith
in
th
is
f
o
r
m
u
la,
(
)
r
ep
r
e
s
en
ts
th
e
weig
h
t
th
at
u
s
er
y
ass
ig
n
s
to
cr
iter
io
n
c
f
o
r
item
i
.
T
h
is
weig
h
t
r
e
f
lects
th
e
im
p
o
r
tan
ce
u
s
er
y
p
lace
s
o
n
c
r
iter
io
n
c
wh
en
e
v
alu
atin
g
item
i
.
(
)
r
ep
r
esen
ts
th
e
s
p
ec
if
ic
r
atin
g
ass
ig
n
ed
b
y
u
s
e
r
y
f
o
r
cr
iter
io
n
c
o
f
item
i
.
S
u
b
s
e
q
u
e
n
t
l
y
,
t
h
e
a
l
g
o
r
i
t
h
m
e
m
p
l
o
y
s
t
w
o
c
o
m
p
l
e
m
e
n
t
a
r
y
m
e
t
r
i
c
s
:
t
h
e
E
u
c
l
i
d
e
a
n
d
i
s
t
a
n
c
e
m
e
t
h
o
d
[
1
8
]
an
d
th
e
R
elev
an
t
J
ac
ca
r
d
m
e
th
o
d
[
1
9
]
,
as
s
h
o
wn
b
y
(
3
)
an
d
(
4
)
,
r
esp
ec
tiv
ely
.
T
h
e
f
o
r
m
er
m
ea
s
u
r
es
th
e
d
is
tan
ce
b
etwe
en
p
r
ed
icted
a
n
d
ac
tu
al
r
atin
g
s
,
wh
ile
th
e
la
tter
ac
co
u
n
ts
f
o
r
t
h
e
co
n
f
id
en
ce
in
th
e
s
im
ilar
ity
ass
es
s
m
en
t b
y
co
n
s
id
er
in
g
th
e
p
r
o
p
o
r
tio
n
o
f
c
o
-
r
ated
item
s
b
etwe
en
u
s
er
s
.
,
=
1
1
+
√
∑
|
,
−
(
)
|
2
∈
∩
(
3
)
W
h
er
e
,
an
d
(
)
r
ep
r
esen
t
t
h
e
p
r
e
d
icted
r
atin
g
a
n
d
t
o
tal
u
tili
ty
o
f
item
i
as
p
er
ce
iv
e
d
b
y
u
s
er
x
,
r
esp
ec
tiv
ely
.
∩
d
en
o
tes th
e
to
tal
n
u
m
b
e
r
o
f
item
s
th
at
b
o
th
u
s
er
s
x
an
d
y
h
av
e
r
ated
.
,
=
1
1
+
(
1
|
∩
|
)
+
(
|
|
−
|
∩
|
1
+
|
|
−
|
∩
|
)
+
(
1
1
+
|
|
−
|
∩
|
)
(
4
)
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.
3
6
,
No
.
3
,
Dec
em
b
er
20
24
:
1
9
1
9
-
1
9
2
8
1922
I
n
th
is
f
o
r
m
u
la,
|
|
|
|
an
d
|
|
s
y
m
b
o
lize
th
e
to
tal
n
u
m
b
er
o
f
item
s
r
ated
b
y
u
s
er
s
x
an
d
y
,
r
esp
ec
tiv
ely
.
T
h
is
f
o
r
m
u
la
es
s
en
tially
ca
lcu
lates
th
e
p
r
o
p
o
r
tio
n
o
f
item
s
th
at
u
s
er
s
x
a
n
d
y
h
av
e
r
ated
in
co
m
m
o
n
r
elativ
e
to
th
e
to
tal
n
u
m
b
er
o
f
item
s
th
ey
h
av
e
ea
ch
r
ated
.
B
u
ild
in
g
u
p
o
n
th
e
c
o
n
ce
p
ts
i
n
tr
o
d
u
ce
d
an
d
f
o
llo
win
g
th
e
ab
o
v
e
ca
lcu
latio
n
s
,
th
e
d
ir
ec
t
tr
u
s
t
s
co
r
e
ass
ig
n
ed
to
th
e
r
elatio
n
s
h
ip
b
e
twee
n
u
s
er
s
x
an
d
y
is
ca
lcu
lat
ed
b
y
co
m
b
in
in
g
th
e
s
im
ilar
ity
m
etr
ics
as
s
h
o
wn
in
th
e
(
5
)
.
,
=
,
×
,
(
5
)
Step
2
:
i
n
f
er
tr
u
s
t sco
r
es f
o
r
u
s
er
s
with
n
o
d
ir
ec
t c
o
n
n
ec
tio
n
W
h
ile
d
ir
ec
t
tr
u
s
t
s
co
r
es
b
etwe
en
u
s
er
s
p
r
o
v
id
e
a
v
alu
ab
le
s
tar
tin
g
p
o
i
n
t,
th
e
r
esu
ltin
g
tr
u
s
t
n
etwo
r
k
o
f
ten
s
u
f
f
e
r
s
f
r
o
m
s
p
ar
s
ity
.
T
h
is
is
d
u
e
to
th
e
co
m
m
o
n
p
h
en
o
m
en
o
n
in
r
ec
o
m
m
e
n
d
er
s
y
s
tem
s
wh
er
e
u
s
er
s
r
ate
o
n
ly
a
lim
ited
s
u
b
s
et
o
f
a
v
ailab
le
item
s
.
T
o
ad
d
r
ess
th
is
lim
itatio
n
an
d
f
u
lly
lev
e
r
ag
e
t
h
e
p
o
ten
tial o
f
tr
u
s
t
n
etwo
r
k
s
,
we
d
r
aw
in
s
p
ir
atio
n
f
r
o
m
s
o
cial
n
etwo
r
k
s
an
d
i
n
c
o
r
p
o
r
ate
t
r
u
s
t p
r
o
p
ag
atio
n
i
n
to
o
u
r
ap
p
r
o
ac
h
.
T
h
is
co
n
ce
p
t
en
ab
les
tr
u
s
t
r
elatio
n
s
h
ip
s
to
b
e
s
p
r
ea
d
th
r
o
u
g
h
in
ter
m
ed
iar
y
u
s
er
s
,
th
er
eb
y
estab
lis
h
in
g
n
o
v
el
in
d
ir
ec
t
co
n
n
ec
tio
n
s
with
in
th
e
tr
u
s
t
n
etwo
r
k
.
B
y
d
o
i
n
g
s
o
,
we
ca
n
f
o
r
m
m
o
r
e
n
u
an
ce
d
tr
u
s
t
r
elatio
n
s
h
ip
s
th
at
s
p
r
ea
d
b
ey
o
n
d
d
ir
ec
t c
o
n
n
ec
ti
o
n
s
b
etwe
en
u
s
er
s
.
T
o
m
ea
s
u
r
e
th
e
lev
el
o
f
tr
u
s
t
p
r
o
p
a
g
ated
b
etwe
en
u
s
er
s
,
we
p
r
o
p
o
s
e
an
a
g
g
r
eg
atio
n
f
u
n
ctio
n
th
at
in
teg
r
ates
co
n
f
id
e
n
ce
weig
h
ts
.
Sp
ec
if
ically
,
th
is
f
u
n
ctio
n
m
ea
s
u
r
es
th
e
tr
u
s
t
f
r
o
m
u
s
er
x
t
o
u
s
er
z
,
m
e
d
iated
b
y
a
co
m
m
o
n
n
eig
h
b
o
r
y
,
as
(
6
)
:
,
Pr
=
∑
(
,
×
,
)
+
(
,
×
,
)
∈
in
te
r
m
e
d
ia
r
y
(
)
∑
,
+
,
∈
in
te
r
m
e
d
ia
r
y
(
)
(
6
)
Step
3
:
d
eter
m
in
e
a
u
s
er
’
s
o
v
e
r
all
tr
u
s
two
r
th
in
ess
T
h
e
o
v
er
all
tr
u
s
t
s
co
r
e
s
er
v
e
s
as
a
cr
u
cial
f
ac
to
r
in
im
p
r
o
v
in
g
th
e
r
ec
o
m
m
en
d
e
r
’
s
c
ap
ac
ity
to
p
r
o
d
u
ce
ac
cu
r
ate
a
n
d
d
i
v
er
s
e
p
r
ed
icted
r
atin
g
s
f
o
r
u
n
k
n
o
wn
item
s
,
m
ain
ly
f
o
r
u
s
er
s
wh
o
h
av
e
lim
ited
co
n
n
ec
tio
n
s
(
n
ea
r
est
n
eig
h
b
o
r
s
)
.
T
h
is
s
co
r
e
aim
s
to
en
h
an
ce
th
e
ac
cu
r
ac
y
an
d
co
v
er
a
g
e
o
f
r
ec
o
m
m
e
n
d
atio
n
p
r
ed
ictio
n
s
,
an
d
ca
n
b
e
d
eter
m
in
ed
b
y
co
m
b
i
n
in
g
two
f
ac
to
r
s
[
2
0
]
:
−
User
r
atin
g
b
eh
a
v
io
r
:
t
h
is
f
ac
t
o
r
m
ea
s
u
r
es h
o
w
m
u
ch
a
u
s
er
’
s
r
atin
g
s
d
ev
iate
f
r
o
m
th
e
av
e
r
ag
e
r
atin
g
s
f
o
r
ea
ch
item
.
A
u
s
er
wh
o
co
n
s
is
ten
tly
r
ates item
s
clo
s
e
to
th
e
a
v
er
ag
e
(
l
o
w
d
ev
iatio
n
)
is
co
n
s
id
er
ed
m
o
r
e
tr
u
s
two
r
th
y
th
an
a
u
s
er
wh
o
c
o
n
s
is
ten
tly
d
ev
iates f
r
o
m
th
e
a
v
er
ag
e
(
h
ig
h
d
ev
iatio
n
)
.
−
User
co
n
n
ec
tiv
ity
:
t
h
is
f
ac
to
r
r
ef
lects
h
o
w
well
-
co
n
n
ec
ted
a
u
s
er
is
wi
th
in
th
e
tr
u
s
t
n
etwo
r
k
.
A
u
s
er
with
h
ig
h
co
n
n
ec
tiv
ity
(
m
o
r
e
c
o
n
n
e
ctio
n
s
)
is
co
n
s
id
er
ed
m
o
r
e
tr
u
s
two
r
th
y
th
an
a
u
s
er
with
lo
w
c
o
n
n
ec
tiv
ity
.
T
h
is
m
ak
es
in
tu
itiv
e
s
en
s
e
as
u
s
er
s
wh
o
co
n
s
is
ten
tly
r
ate
item
s
clo
s
e
to
th
e
av
er
ag
e
a
n
d
h
av
e
a
wid
er
n
etwo
r
k
o
f
co
n
n
ec
tio
n
s
ar
e
lik
ely
to
b
e
m
o
r
e
r
eliab
le
s
o
u
r
ce
s
o
f
r
ec
o
m
m
en
d
atio
n
s
.
T
h
e
o
v
er
all
tr
u
s
t
s
co
r
e
f
o
r
a
u
s
er
x
is
m
ea
s
u
r
ed
as
(
7
)
.
=
(
−
∑
|
,
−
̄
|
∈
|
|
)
×
√
|
|
|
|
(
7
)
w
h
er
e
,
,
ex
em
p
lifie
s
th
e
av
e
r
ag
e
r
atin
g
g
iv
en
b
y
u
s
er
x
a
cr
o
s
s
all
ev
alu
atio
n
cr
iter
ia
f
o
r
item
i
,
̄
s
ig
n
if
ies
th
e
m
ea
n
r
atin
g
ac
r
o
s
s
all
u
s
er
s
f
o
r
item
i
,
co
n
s
id
er
in
g
all
ev
alu
atio
n
cr
iter
ia,
an
d
|
|
is
th
e
n
u
m
b
er
o
f
u
s
er
s
wh
o
a
r
e
co
n
n
ec
ted
to
u
s
er
x
with
in
th
e
u
s
er
s
’
tr
u
s
t n
etwo
r
k
.
Step
4
:
c
o
m
p
u
te
th
e
u
s
er
-
b
ased
tr
u
s
t
-
en
h
a
n
ce
d
p
r
ed
icted
r
ati
n
g
s
T
h
e
f
in
al
s
tep
in
th
is
m
o
d
u
le
co
m
p
r
is
es
g
en
er
atin
g
p
r
e
d
icted
r
atin
g
s
f
o
r
an
ac
tiv
e
u
s
er
x
o
n
a
tar
g
et
item
i
b
y
in
co
r
p
o
r
atin
g
th
e
d
i
r
ec
t,
p
r
o
p
a
g
ated
,
an
d
o
v
er
all
tr
u
s
t
v
alu
es
o
f
h
is
n
ea
r
est
n
eig
h
b
o
r
s
N
N
(
x)
in
to
th
e
weig
h
ted
av
er
a
g
e
[
2
1
]
,
as
(
8
)
.
,
=
{
̅
+
∑
,
×
(
,
−
̅
̅
̅
)
∈
(
)
∑
,
∈
(
)
;
,
≠
0
̅
+
∑
×
(
,
−
̅
̅
̅
)
∈
(
)
∑
∈
(
)
;
,
≠
0
}
(
8
)
2
.
2
.
T
he
I
t
em
-
ba
s
ed
m
ulti
-
c
rit
er
ia
t
rus
t
-
enha
nced
CF
m
o
du
le
T
o
g
en
er
ate
r
ec
o
m
m
en
d
atio
n
s
th
at
co
n
s
id
er
th
e
tr
u
s
t
r
elatio
n
s
h
ip
s
b
etwe
en
item
s
,
th
is
m
o
d
u
le
lev
er
ag
es
b
o
t
h
th
e
item
s
’
tr
u
s
t
n
etwo
r
k
an
d
ea
ch
item
’
s
o
v
e
r
all
tr
u
s
t
s
co
r
e.
T
h
is
p
r
o
ce
s
s
ca
n
b
e
b
r
o
k
en
d
o
wn
in
to
th
r
ee
m
ain
s
tep
s
:
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
A
mu
lti
-
crit
eria
tr
u
s
t
-
en
h
a
n
ce
d
co
lla
b
o
r
a
tive
filt
erin
g
a
lg
o
r
ith
m
…
(
Qu
s
a
i Y.
S
h
a
m
b
o
u
r
)
1923
Step
1
:
a
s
s
ig
n
tr
u
s
t v
alu
es f
o
r
item
s
b
ased
o
n
th
eir
in
te
r
ac
tio
n
s
C
o
n
tin
u
in
g
with
th
e
r
atio
n
a
le
estab
lis
h
ed
in
th
e
p
r
ev
io
u
s
m
o
d
u
le,
th
is
m
eth
o
d
u
ti
lizes
two
co
m
p
lem
en
tar
y
m
etr
ics
f
o
r
t
r
u
s
t
s
co
r
e
ca
lcu
latio
n
b
etwe
e
n
item
s
:
th
e
E
u
clid
ea
n
d
is
tan
ce
m
etr
ic
an
d
th
e
R
elev
an
t Jacc
ar
d
m
etr
ic.
T
h
es
e
m
etr
ics ar
e
p
r
esen
ted
in
E
q
u
atio
n
s
(
9
)
an
d
(
1
0
)
,
r
esp
ec
tiv
ely
.
T
h
e
E
u
clid
ea
n
d
is
tan
ce
m
et
h
o
d
f
o
cu
s
es
o
n
th
e
m
ag
n
itu
d
e
o
f
th
e
d
if
f
er
en
ce
b
etwe
en
p
r
ed
icted
r
atin
g
s
an
d
ac
tu
al
u
s
er
r
atin
g
s
.
I
n
s
im
p
ler
ter
m
s
,
it
ca
lcu
lates
h
o
w
clo
s
e
th
e
p
r
e
d
icted
v
a
lu
es
ar
e
to
t
h
e
r
ea
l
u
s
er
r
atin
g
s
.
,
=
1
1
+
√
∑
|
,
−
(
)
|
2
∈
∩
(
8
)
w
h
er
e
∩
s
ig
n
if
ies th
e
n
u
m
b
er
o
f
u
s
er
s
th
at
h
av
e
p
r
o
v
i
d
ed
r
atin
g
s
f
o
r
b
o
th
item
s
i
an
d
j
.
T
h
e
R
elev
an
t
J
ac
ca
r
d
m
eth
o
d
,
o
n
th
e
o
th
er
h
an
d
,
tak
es
i
n
to
ac
co
u
n
t
th
e
co
n
f
i
d
en
ce
l
ev
el
in
th
e
s
im
ilar
ity
ass
e
s
s
m
en
t
b
etwe
en
item
s
.
I
t
ac
h
iev
es
th
is
b
y
co
n
s
id
er
in
g
th
e
p
r
o
p
o
r
tio
n
o
f
u
s
er
s
th
at
h
av
e
r
ated
b
o
th
item
s
.
A
h
ig
h
er
p
r
o
p
o
r
tio
n
o
f
c
o
-
r
ated
u
s
er
s
s
u
g
g
ests
a
m
o
r
e
r
eliab
le
ass
ess
m
en
t o
f
item
s
im
ilar
ity
.
,
=
1
1
+
(
1
|
∩
|
)
+
(
|
|
−
|
∩
|
1
+
|
|
−
|
∩
|
)
+
(
1
1
+
|
|
−
|
∩
|
)
(
9
)
W
h
er
e
|
U
i
|
r
ep
r
esen
ts
th
e
en
tire
am
o
u
n
t o
f
u
s
er
s
wh
o
h
a
v
e
r
ated
item
i
.
Fo
llo
win
g
th
is
,
th
e
tr
u
s
t
s
co
r
e
b
etwe
en
item
s
i
an
d
j
is
ca
lcu
lated
b
y
co
m
b
i
n
in
g
th
e
s
im
ilar
ity
m
etr
ics as sh
o
wn
in
th
e
(
1
1
)
.
,
=
,
×
,
(
10
)
Step
2
:
d
eter
m
in
e
a
n
item
’
s
o
v
er
all
tr
u
s
two
r
th
in
ess
T
o
ad
d
r
ess
th
e
ch
allen
g
e
o
f
s
p
ar
s
ity
,
p
ar
ticu
lar
ly
f
o
r
item
s
with
lim
ited
r
atin
g
s
,
we
p
r
o
p
o
s
e
an
o
v
er
all
tr
u
s
t
s
co
r
e
f
o
r
ea
ch
item
.
T
h
is
s
co
r
e
aim
s
to
en
h
an
ce
th
e
ac
cu
r
ac
y
an
d
co
v
e
r
ag
e
o
f
r
ec
o
m
m
e
n
d
atio
n
p
r
ed
ictio
n
s
.
T
h
e
o
v
e
r
all
s
im
ilar
ity
s
co
r
e
is
ca
lcu
lated
b
y
co
n
s
id
er
in
g
two
k
ey
f
ac
to
r
s
:
−
I
tem
r
atin
g
b
eh
a
v
io
r
:
t
h
is
f
ac
t
o
r
m
ea
s
u
r
es
th
e
d
is
p
er
s
io
n
o
f
u
s
er
r
atin
g
s
f
o
r
a
s
p
ec
if
ic
ite
m
co
m
p
a
r
ed
to
th
e
av
er
ag
e
r
atin
g
ac
r
o
s
s
all
it
em
s
.
A
s
m
aller
d
ev
iatio
n
in
d
i
ca
tes
th
at
th
e
item
’
s
r
atin
g
s
te
n
d
to
b
e
clo
s
er
to
th
e
g
en
e
r
al
u
s
er
p
r
ef
er
en
ce
.
−
I
tem
co
n
n
ec
ti
v
ity
:
th
is
f
ac
to
r
r
ef
lects
th
e
n
u
m
b
er
o
f
co
n
n
e
ctio
n
s
an
item
h
as
with
in
th
e
item
-
item
tr
u
s
t
n
etwo
r
k
.
A
h
ig
h
er
n
u
m
b
er
o
f
co
n
n
ec
tio
n
s
s
u
g
g
ests
th
e
item
is
r
elate
d
to
a
b
r
o
ad
er
r
an
g
e
o
f
o
th
e
r
item
s
,
p
o
ten
tially
in
d
icatin
g
its
o
v
er
a
ll lev
el
o
f
u
s
er
en
g
ag
em
e
n
t.
B
y
in
co
r
p
o
r
atin
g
th
ese
f
ac
to
r
s
,
an
item
with
b
o
th
lo
w
d
ev
iatio
n
an
d
h
ig
h
co
n
n
ec
tiv
ity
r
ec
eiv
es
a
h
ig
h
er
o
v
er
all
tr
u
s
t
s
co
r
e,
wh
ich
ca
n
im
p
r
o
v
e
th
e
r
ec
o
m
m
e
n
d
atio
n
s
y
s
tem
’
s
ab
ilit
y
to
s
u
g
g
est
r
elev
an
t
item
s
,
esp
ec
ially
f
o
r
th
o
s
e
with
lim
it
ed
r
atin
g
s
.
T
h
e
o
v
e
r
all
tr
u
s
t sco
r
e
f
o
r
an
item
i
is
m
ea
s
u
r
e
d
a
s
(
1
2
)
.
=
(
−
∑
|
,
−
̄
|
∈
|
|
)
×
√
|
|
|
|
(
11
)
I
n
th
is
f
o
r
m
u
la,
̄
r
ep
r
esen
ts
th
e
m
ea
n
r
atin
g
ac
r
o
s
s
all
item
s
o
f
u
s
er
x
,
co
n
s
id
er
in
g
all
ev
alu
atio
n
cr
iter
ia
,
an
d
|
U
i
|
s
ig
n
if
ies
th
e
to
tal
n
u
m
b
e
r
o
f
u
s
er
s
wh
o
h
av
e
r
ated
item
i
.
Ad
d
itio
n
ally
,
|
I
i
|
is
th
e
n
u
m
b
er
o
f
item
s
co
n
n
ec
ted
to
item
i
with
in
th
e
item
s
’
tr
u
s
t
n
etwo
r
k
.
Fin
ally
,
|
I
|
r
ep
r
esen
ts
th
e
to
tal
n
u
m
b
er
o
f
item
s
in
th
e
en
tire
d
ataset.
Step
3
:
c
o
m
p
u
te
th
e
item
-
b
ase
d
tr
u
s
t
-
en
h
a
n
ce
d
p
r
ed
icted
r
ati
n
g
s
T
h
is
s
tep
in
v
o
lv
es
g
e
n
er
atin
g
p
r
ed
icted
r
atin
g
s
f
o
r
an
ac
tiv
e
u
s
er
x
o
n
a
tar
g
et
item
i
.
T
h
is
p
r
ed
ictio
n
lev
er
ag
es
b
o
th
t
h
e
d
ir
ec
t
tr
u
s
t
s
co
r
es
an
d
th
e
o
v
er
all
tr
u
s
t
s
co
r
es
as
s
ig
n
ed
to
a
tar
g
et
item
i
’
s
n
ea
r
est
n
eig
h
b
o
r
s
N
N
(
i)
in
to
th
e
weig
h
ted
av
er
a
g
e,
as
(
1
3
)
.
,
=
{
̅
+
∑
,
×
(
,
−
̅
)
∈
(
)
∑
,
∈
(
)
;
,
≠
0
̅
+
∑
×
(
,
−
̅
)
∈
(
)
∑
∈
(
)
;
,
≠
0
}
(
1
3
)
2
.
3
.
T
he
hy
brid re
co
m
m
end
a
t
io
n m
o
du
le
Fo
llo
win
g
th
e
s
u
cc
ess
o
f
co
m
b
in
in
g
m
u
ltip
le
r
ec
o
m
m
en
d
atio
n
tech
n
iq
u
es
[
2
2
]
,
th
is
m
o
d
u
le
u
tili
ze
s
a
d
y
n
a
m
ic
s
witch
in
g
a
p
p
r
o
ac
h
.
T
h
is
a
p
p
r
o
ac
h
s
elec
ts
th
e
m
o
s
t
s
u
itab
le
p
r
e
d
ictio
n
m
et
h
o
d
o
n
th
e
f
ly
,
b
ased
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.
3
6
,
No
.
3
,
Dec
em
b
er
20
24
:
1
9
1
9
-
1
9
2
8
1924
o
n
its
ab
ilit
y
to
p
r
e
d
ict
r
atin
g
s
f
o
r
u
n
s
ee
n
item
s
.
T
h
e
u
ltima
te
g
o
al
is
to
im
p
r
o
v
e
b
o
t
h
th
e
ac
c
u
r
ac
y
an
d
co
v
er
ag
e
o
f
th
e
r
ec
o
m
m
en
d
ati
o
n
s
.
T
h
e
k
ey
f
ac
to
r
in
th
is
s
el
ec
tio
n
p
r
o
ce
s
s
is
th
e
ab
ilit
y
to
p
r
ed
ict
r
atin
g
s
f
o
r
item
s
th
e
u
s
er
h
asn
’
t
s
ee
n
b
ef
o
r
e
(
u
n
s
ee
n
item
s
)
.
T
h
e
m
o
d
u
le
em
p
lo
y
s
th
e
r
o
o
t
m
ea
n
s
q
u
ar
e
(
R
MS)
m
etr
ic
wh
en
b
o
th
ca
n
d
id
ate
m
eth
o
d
s
ca
n
p
r
ed
ict
u
n
s
ee
n
item
s
.
T
h
is
m
etr
ic
h
elp
s
q
u
a
n
tify
t
h
e
lev
el
o
f
ag
r
ee
m
en
t
b
etwe
en
th
e
two
p
r
ed
icted
r
ati
n
g
s
,
lead
in
g
t
o
m
o
r
e
r
o
b
u
s
t a
n
d
r
eliab
le
r
ec
o
m
m
en
d
atio
n
s
.
,
=
{
0
;
if
,
=
0
a
n
d
,
=
0
,
;
if
,
≠
0
a
n
d
,
=
0
,
;
if
,
=
0
a
n
d
,
≠
0
√
(
,
)
2
+
(
,
)
2
2
;
if
,
≠
0
a
n
d
,
≠
0
}
(
12
)
3.
E
XP
E
R
I
M
E
N
T
S
3
.
1
.
Da
t
a
s
et
s
a
nd
ev
a
lua
t
io
n
m
et
ho
d
I
n
ev
alu
atin
g
o
u
r
p
r
o
p
o
s
ed
alg
o
r
ith
m
,
we
u
tili
ze
d
two
MC
r
atin
g
d
atasets
o
b
tain
ed
f
r
o
m
th
e
T
r
ip
Ad
v
is
o
r
to
u
r
is
m
p
latf
o
r
m
:
th
e
r
estau
r
an
ts
d
ataset
an
d
t
h
e
Ho
tels
r
atin
g
d
ataset
[
2
3
]
.
T
h
e
r
estau
r
an
ts
MC
d
ataset
co
n
s
is
t
s
o
f
r
atin
g
s
p
r
o
v
id
ed
b
y
u
s
er
s
f
o
r
v
a
r
io
u
s
r
estau
r
an
ts
.
User
s
r
ated
th
ese
r
es
tau
r
an
ts
o
n
a
s
ca
le
o
f
1
to
5
ac
r
o
s
s
th
r
ee
c
r
iter
ia:
s
er
v
ice,
f
o
o
d
,
a
n
d
v
alu
e.
T
h
is
d
ataset
co
n
tain
s
a
to
tal
o
f
1
4
,
6
3
3
r
atin
g
s
co
n
tr
ib
u
ted
b
y
1
,
2
5
4
u
s
er
s
f
o
r
2
0
5
r
estau
r
a
n
ts
.
T
h
e
Ho
tels
MC
d
ataset,
o
n
th
e
o
th
er
h
an
d
,
co
n
s
is
ts
o
f
r
atin
g
s
p
r
o
v
id
e
d
b
y
u
s
er
s
f
o
r
n
u
m
er
o
u
s
h
o
tels
.
User
s
wer
e
a
b
le
to
r
ate
h
o
tels
o
n
a
s
ca
le
o
f
1
t
o
5
b
ased
o
n
s
ev
e
n
cr
iter
ia:
v
alu
e
f
o
r
m
o
n
ey
,
q
u
al
ity
o
f
r
o
o
m
s
,
lo
ca
tio
n
o
f
th
e
h
o
tel,
clea
n
lin
ess
o
f
th
e
h
o
tel,
q
u
ality
o
f
ch
ec
k
-
i
n
,
o
v
er
all
q
u
ality
o
f
s
er
v
ices,
an
d
q
u
ality
o
f
b
u
s
in
ess
s
er
v
ices.
T
h
is
d
ataset
co
m
p
r
is
es
2
8
,
8
2
9
r
atin
g
s
p
r
o
v
id
ed
b
y
1
,
0
3
9
u
s
er
s
f
o
r
6
9
3
h
o
tels
.
T
o
d
em
o
n
s
tr
ate
th
e
ef
f
ec
tiv
en
ess
o
f
o
u
r
p
r
o
p
o
s
ed
alg
o
r
ith
m
,
we
em
p
lo
y
two
wid
ely
ad
o
p
t
ed
m
etr
ics
in
th
e
f
ield
o
f
r
ec
o
m
m
en
d
e
r
s
y
s
tem
s
:
m
ea
n
ab
s
o
lu
te
er
r
o
r
(
MA
E
)
an
d
co
v
e
r
ag
e
r
ate
.
MA
E
is
a
co
m
m
o
n
ly
u
s
ed
m
ea
s
u
r
e
f
o
r
e
v
alu
atin
g
p
r
ed
ictio
n
ac
c
u
r
ac
y
.
I
t
q
u
an
ti
f
ies
th
e
av
er
ag
e
ab
s
o
lu
te
d
ev
iatio
n
b
etwe
en
th
e
p
r
ed
icted
r
atin
g
s
an
d
th
e
ac
tu
a
l
r
atin
g
s
o
f
th
e
tar
g
et
item
s
.
A
lo
wer
MA
E
v
alu
e
in
d
icate
s
a
h
ig
h
er
ac
cu
r
ac
y
o
f
th
e
r
ec
o
m
m
e
n
d
er
s
y
s
tem
in
p
r
ed
ictin
g
r
atin
g
s
.
C
o
v
er
a
g
e
r
ate,
o
n
t
h
e
o
th
e
r
h
a
n
d
,
is
u
t
ilized
to
ass
ess
th
e
d
iv
er
s
ity
o
f
th
e
r
ec
o
m
m
en
d
atio
n
r
esu
lts
,
p
ar
ticu
lar
ly
in
s
itu
atio
n
s
wh
er
e
d
ata
s
p
ar
s
ity
is
a
ch
allen
g
e.
T
h
is
m
etr
ic
m
ea
s
u
r
es
th
e
ab
i
lity
o
f
a
r
ec
o
m
m
en
d
atio
n
m
e
th
o
d
to
g
en
er
ate
p
r
ed
ictio
n
s
f
o
r
a
d
iv
er
s
e
s
et
o
f
item
s
,
in
clu
d
in
g
th
o
s
e
th
at
h
a
v
e
n
o
t
b
ee
n
r
ated
o
r
ar
e
n
ewl
y
in
tr
o
d
u
ce
d
.
I
t
r
e
p
r
esen
ts
th
e
p
r
o
p
o
r
tio
n
o
f
all
av
ailab
le
item
s
th
at
ca
n
b
e
r
ec
o
m
m
en
d
e
d
.
A
h
ig
h
er
c
o
v
er
a
g
e
r
ate
s
ig
n
if
ies
t
h
at
th
e
r
ec
o
m
m
en
d
atio
n
m
o
d
el
is
ca
p
ab
le
o
f
s
u
g
g
esti
n
g
a
wid
e
r
v
ar
iety
o
f
item
s
with
in
t
h
e
av
a
ilab
le
d
ata,
ev
e
n
in
cl
u
d
in
g
n
e
w
o
r
u
n
r
ated
item
s
.
T
h
is
en
h
an
ce
s
t
h
e
d
iv
er
s
ity
i
n
g
e
n
er
atin
g
p
er
s
o
n
alize
d
r
ec
o
m
m
en
d
atio
n
s
an
d
m
itig
ates
th
e
im
p
ac
t
o
f
d
ata
s
p
ar
s
ity
[
2
4
]
.
I
n
o
u
r
e
v
alu
atio
n
,
we
ass
ess
e
d
th
e
p
er
f
o
r
m
an
ce
o
f
p
r
o
p
o
s
e
d
HM
C
T
eCF
alg
o
r
ith
m
b
y
co
m
p
ar
in
g
it
with
f
o
u
r
b
e
n
ch
m
ar
k
C
F
-
b
ased
ap
p
r
o
ac
h
es:
i
)
t
h
e
m
u
lti
-
c
r
iter
ia
u
s
er
-
b
ased
C
F
ap
p
r
o
ac
h
(
MC
-
UC
F)
[
1
8
]
,
wh
ich
em
p
lo
y
s
th
e
s
im
ilar
ity
-
b
ased
ap
p
r
o
ac
h
to
in
co
r
p
o
r
ate
an
d
lev
er
ag
e
m
u
lti
-
c
r
iter
ia
r
atin
g
b
etwe
en
u
s
er
s
to
im
p
r
o
v
e
r
ec
o
m
m
en
d
atio
n
ac
cu
r
ac
y
;
ii
)
th
e
m
u
lti
-
cr
iter
ia
item
-
b
ased
C
F
alg
o
r
ith
m
(
MC
-
I
C
F)
[
1
8
]
,
wh
ich
s
im
ilar
ly
u
s
es
th
e
s
im
ilar
ity
-
b
ased
ap
p
r
o
ac
h
b
u
t
f
o
cu
s
es
o
n
in
co
r
p
o
r
atin
g
a
n
d
lev
e
r
ag
in
g
m
u
lti
-
cr
iter
ia
r
atin
g
s
b
etwe
en
item
s
to
im
p
r
o
v
e
r
ec
o
m
m
en
d
atio
n
ac
c
u
r
ac
y
;
iii
)
th
e
m
u
lti
-
cr
iter
ia
u
s
er
-
item
b
ased
C
F
ap
p
r
o
ac
h
(
MC
-
UI
C
F),
a
h
y
b
r
id
ap
p
r
o
ac
h
th
at
co
m
b
in
es
th
e
p
r
in
cip
les
o
f
MC
-
UC
F
an
d
MC
-
I
C
F
to
lev
er
ag
e
u
s
er
an
d
item
m
u
lti
-
cr
iter
ia
r
atin
g
s
f
o
r
en
h
an
ce
d
r
ec
o
m
m
en
d
atio
n
s
;
an
d
iv
)
th
e
MC
tr
u
s
t
-
en
h
an
ce
d
C
F
(
MC
-
T
eCF
)
ap
p
r
o
ac
h
[
2
5
]
,
w
h
ich
s
ee
k
s
to
im
p
r
o
v
e
p
r
e
d
ictiv
e
ac
cu
r
ac
y
an
d
ad
d
r
ess
is
s
u
es
o
f
d
ata
s
p
a
r
s
ity
an
d
c
o
ld
-
s
tar
t
u
s
er
s
b
y
u
tili
zin
g
m
u
lti
-
cr
iter
ia
r
atin
g
s
in
co
n
ju
n
ctio
n
with
in
f
er
r
ed
tr
u
s
t
r
elatio
n
s
h
ip
s
am
o
n
g
u
s
er
s
.
3
.
2
.
Co
m
pa
riso
n o
f
re
c
o
mm
enda
t
io
n a
pp
ro
a
ches
T
h
is
s
ec
tio
n
p
r
o
v
id
es
a
d
etai
led
co
m
p
ar
ativ
e
a
n
aly
s
is
o
f
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
’
s
p
er
f
o
r
m
an
ce
,
co
m
p
ar
in
g
it
to
b
en
ch
m
ar
k
a
p
p
r
o
ac
h
es
ac
r
o
s
s
two
k
ey
m
e
tr
ics:
p
r
ed
ictio
n
ac
cu
r
ac
y
a
n
d
co
v
e
r
ag
e
r
ate.
T
h
e
an
aly
s
is
is
b
ased
o
n
a
s
er
ies o
f
ex
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im
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h
ly
ev
alu
ate
th
e
alg
o
r
ith
m
’
s
ef
f
ec
tiv
en
ess
.
3
.
2
.
1
.
E
v
a
lua
t
io
n o
f
predict
io
n a
cc
ura
cy
us
ing
t
o
uris
m
-
r
ela
t
ed
da
t
a
s
et
s
T
h
e
e
v
al
u
a
ti
o
n
o
f
th
e
p
r
o
p
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s
ed
HM
C
T
eCF
al
g
o
r
it
h
m
’
s
p
r
e
d
ic
ti
o
n
a
cc
u
r
a
cy
o
n
t
wo
r
e
al
-
wo
r
l
d
d
at
ase
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f
r
o
m
t
h
e
T
r
ip
Ad
v
is
o
r
to
u
r
is
m
p
lat
f
o
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m
,
t
h
e
R
esta
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r
an
ts
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n
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th
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H
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d
a
taset
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h
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s
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its
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f
e
cti
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e
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s
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m
p
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t
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h
m
ar
k
a
p
p
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a
c
h
es
i
n
c
lu
d
i
n
g
MC
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F,
MC
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I
C
F
,
MC
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UI
C
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a
n
d
MC
-
T
eCF
.
T
h
is
e
v
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ati
o
n
c
o
v
er
s
v
a
r
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o
u
s
s
i
ze
s
o
f
n
e
a
r
est
n
ei
g
h
b
o
r
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
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J
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g
&
C
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p
Sci
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2
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-
4
7
52
A
mu
lti
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crit
eria
tr
u
s
t
-
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h
a
n
ce
d
co
lla
b
o
r
a
tive
filt
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g
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lg
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r
ith
m
…
(
Qu
s
a
i Y.
S
h
a
m
b
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r
)
1925
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h
e
r
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l
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r
est
a
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r
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t
s
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s
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o
w
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i
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Fi
g
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,
d
e
m
o
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s
t
r
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ic
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cr
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iz
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n
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ar
est
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e
ig
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o
r
s
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f
r
o
m
5
to
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0
,
th
e
HM
C
T
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c
o
n
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te
n
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ly
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t
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r
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h
m
a
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k
ap
p
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h
es
,
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n
cl
u
d
in
g
MC
-
U
C
F,
MC
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I
C
F
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MC
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UI
C
F
,
a
n
d
MC
-
T
eCF
.
T
h
e
t
r
e
n
d
o
f
s
u
p
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r
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f
o
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m
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ce
co
n
ti
n
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es
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cr
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s
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al
l
n
ei
g
h
b
o
r
s
iz
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wi
th
H
MCTe
C
F
a
ch
ie
v
i
n
g
t
h
e
l
o
w
est
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E
o
f
0
.
9
7
5
at
2
5
n
ei
g
h
b
o
r
s
.
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e
r
a
ll
,
t
h
e
av
er
a
g
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MA
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o
f
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C
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is
0
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9
8
2
,
r
e
p
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ti
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g
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1
6
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p
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v
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en
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a
1
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%
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p
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m
e
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r
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a
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%
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m
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I
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a
n
d
a
4
%
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m
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m
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n
t
o
v
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r
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T
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m
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n
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t
t
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h
m
’
s
e
f
f
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t
h
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r
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r
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ati
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ai
n
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T
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r
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a
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F
ig
u
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e
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,
f
u
r
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r
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g
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m
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ch
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a
r
k
ap
p
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h
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b
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s
u
b
s
t
an
t
ial
m
a
r
g
i
n
.
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h
is
h
ig
h
lig
h
ts
th
e
ef
f
ec
tiv
en
ess
o
f
th
e
HM
C
T
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F
alg
o
r
ith
m
in
p
r
o
v
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d
in
g
m
o
r
e
ac
cu
r
ate
r
ec
o
m
m
en
d
atio
n
s
.
T
h
e
HM
C
T
eC
F
alg
o
r
ith
m
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n
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is
ten
tly
o
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o
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ed
th
e
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en
ch
m
ar
k
s
ac
r
o
s
s
v
ar
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u
s
s
izes
o
f
n
ea
r
est
n
eig
h
b
o
r
s
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with
th
e
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o
s
t
n
o
tab
le
g
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s
at
s
m
aller
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eig
h
b
o
r
s
izes,
cr
u
cial
f
o
r
a
d
d
r
ess
in
g
d
ata
s
p
ar
s
ity
,
wh
er
e
tr
ad
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al
C
F
-
b
ased
ap
p
r
o
ac
h
e
s
o
f
ten
s
tr
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g
g
le.
As th
e
n
u
m
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er
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h
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o
r
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in
cr
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s
es,
th
e
M
AE
o
f
HM
C
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n
tin
u
es t
o
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em
ain
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with
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s
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ch
as
0
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7
2
2
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o
r
1
0
n
eig
h
b
o
r
s
an
d
0
.
7
1
0
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o
r
2
0
n
eig
h
b
o
r
s
.
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h
e
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s
est
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m
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etito
r
,
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T
eCF
,
h
as
co
r
r
esp
o
n
d
in
g
MA
E
s
o
f
0
.
8
4
3
an
d
0
.
8
2
7
,
r
esp
ec
tiv
ely
.
On
av
er
ag
e
,
th
e
HM
C
T
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s
h
o
ws
th
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h
ig
h
est
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er
ce
n
tag
e
im
p
r
o
v
em
e
n
t
in
MA
E
co
m
p
ar
ed
to
MC
-
UC
F
(
4
0
%),
f
o
llo
wed
b
y
MC
-
I
C
F
(
2
9
%),
MC
-
UI
C
F
(
1
8
%),
a
n
d
MC
-
T
eCF
(
1
4
%).
T
h
ese
im
p
r
o
v
em
en
ts
h
ig
h
lig
h
t
th
e
ef
f
ec
tiv
en
ess
an
d
ac
cu
r
ac
y
o
f
HM
C
T
eCF
in
p
r
ed
ictin
g
u
s
er
p
r
ef
e
r
en
ce
s
f
o
r
h
o
tel
r
ec
o
m
m
en
d
atio
n
s
.
1
Fig
u
r
e
1
.
T
h
e
MA
E
p
er
f
o
r
m
a
n
ce
o
n
t
h
e
r
estau
r
an
t’
s
d
ataset
with
v
ar
y
in
g
n
ea
r
est
n
eig
h
b
o
r
s
izes
Fig
u
r
e
2
.
T
h
e
MA
E
p
er
f
o
r
m
a
n
ce
o
n
t
h
e
Ho
tels
d
ataset
with
v
ar
y
in
g
n
ea
r
est n
eig
h
b
o
r
s
izes
3
.
2
.
2
.
E
v
a
lua
t
io
n o
f
predict
io
n a
cc
ura
cy
a
nd
co
v
er
a
g
e
r
a
t
e
a
cr
o
s
s
v
a
ry
ing
le
v
els o
f
s
pa
rsity
T
o
ass
ess
t
h
e
r
o
b
u
s
t
n
ess
o
f
th
e
p
r
o
p
o
s
ed
HM
C
T
eCF
al
g
o
r
i
t
h
m
i
n
h
a
n
d
li
n
g
d
at
a
s
p
a
r
s
it
y
,
a
c
o
m
m
o
n
ch
all
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e
i
n
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o
m
m
en
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tem
s
,
w
e
e
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ate
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its
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e
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f
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m
a
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x
d
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h
v
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r
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in
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le
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f
s
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r
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it
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,
r
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g
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n
g
f
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o
m
9
9
.
8
%
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o
9
8
.
0
%
.
T
h
e
m
a
in
g
o
al
w
as
t
o
ass
ess
t
h
e
ca
p
a
cit
y
o
f
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h
e
c
o
m
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d
a
p
p
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a
ch
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n
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le
v
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n
g
le
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ls
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t
a
s
p
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r
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n
d
t
o
e
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a
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ate
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es
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e
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f
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m
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n
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n
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h
at
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n
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ex
t.
Fig
u
r
es
3
a
n
d
4
il
lu
s
tr
ate
t
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e
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p
e
r
i
o
r
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e
r
f
o
r
m
a
n
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e
o
f
t
h
e
H
MCTe
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a
lg
o
r
it
h
m
in
te
r
m
s
o
f
MA
E
a
n
d
C
o
v
er
a
g
e
r
at
e
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o
m
p
ar
e
d
t
o
t
h
e
b
e
n
ch
m
a
r
k
a
p
p
r
o
ac
h
es
.
A
s
s
h
o
wn
b
y
Fi
g
u
r
e
3
,
as
t
h
e
l
ev
el
o
f
s
p
ar
s
it
y
d
e
cr
ea
s
es
(
f
r
o
m
9
9
.
8
%
to
9
8
.
0
%
)
,
HM
C
T
eCF
m
ai
n
ta
in
s
t
h
e
l
o
wes
t
M
AE
v
al
u
es
c
o
m
p
ar
ed
t
o
o
th
er
ap
p
r
o
ac
h
es
.
A
t
9
9
.
8
%
s
p
a
r
s
it
y
,
HM
C
T
eCF
ac
h
ie
v
es
a
n
M
A
E
o
f
1
.
3
0
2
,
s
i
g
n
if
ica
n
t
ly
b
ett
e
r
t
h
a
n
t
h
e
n
e
x
t
b
es
t
(
MC
-
T
eCF
)
wi
th
2
.
7
3
1
.
T
h
is
tr
e
n
d
c
o
n
ti
n
u
es
ac
r
o
s
s
all
s
p
ar
s
ity
le
v
els
,
wi
th
HM
C
T
eCF
a
ch
i
e
v
i
n
g
th
e
l
o
wes
t
MA
E
o
f
0
.
6
6
8
at
9
8
.
0
%
s
p
a
r
s
i
ty
.
T
h
e
p
r
o
p
o
s
e
d
al
g
o
r
i
th
m
s
h
o
ws
s
u
b
s
ta
n
ti
al
i
m
p
r
o
v
e
m
e
n
ts
,
es
p
ec
i
all
y
i
n
h
i
g
h
-
s
p
a
r
s
it
y
s
ce
n
a
r
i
o
s
.
F
o
r
e
x
a
m
p
l
e,
a
t
a
s
p
a
r
s
i
ty
le
v
el
o
f
9
9
.
8
%,
th
e
p
r
o
p
o
s
ed
al
g
o
r
i
th
m
s
h
o
ws
an
i
m
p
r
o
v
e
m
e
n
t
o
f
ar
o
u
n
d
6
7
%
o
v
e
r
t
h
e
MC
-
UC
F,
MC
-
I
C
F
,
an
d
MC
-
U
I
C
F
a
p
p
r
o
ac
h
es
,
a
n
d
ap
p
r
o
x
im
ate
ly
5
2
%
o
v
er
t
h
e
MC
-
T
eCF
a
p
p
r
o
a
c
h
.
T
h
e
l
ar
g
e
p
e
r
ce
n
ta
g
e
i
m
p
r
o
v
e
m
e
n
ts
at
t
h
e
9
9
.
8
%
s
p
a
r
s
it
y
le
v
el
a
d
v
is
e
t
h
e
p
r
o
p
o
s
e
d
a
p
p
r
o
a
ch
is
p
a
r
ti
cu
la
r
l
y
well
-
s
u
it
e
d
f
o
r
a
p
p
lic
ati
o
n
s
wit
h
v
er
y
li
m
it
e
d
d
ata
a
v
a
ila
b
i
lit
y
.
I
n
te
r
m
s
o
f
co
v
er
ag
e
r
at
e
,
as
d
ep
i
ct
ed
i
n
Fi
g
u
r
e
4
,
t
h
e
H
MC
T
eCF
e
x
c
els
i
n
te
r
m
s
o
f
c
o
v
e
r
ag
e
ac
r
o
s
s
all
s
p
a
r
s
i
ty
le
v
e
ls
.
At
9
9
.
8
%
s
p
a
r
s
it
y
,
i
t
a
ch
ie
v
es
a
co
v
er
ag
e
o
f
8
9
%,
f
a
r
e
x
ce
e
d
i
n
g
t
h
e
n
e
x
t
b
es
t
(
MC
-
T
eCF
)
wit
h
4
1
%.
T
h
is
h
i
g
h
c
o
v
e
r
a
g
e
r
a
te
is
m
ai
n
ta
in
e
d
ev
e
n
at
lo
w
er
s
p
a
r
s
it
y
l
ev
els
,
in
d
i
ca
t
i
n
g
t
h
e
al
g
o
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it
h
m
’
s
ab
i
lit
y
t
o
p
r
o
v
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d
e
r
e
le
v
a
n
t
r
ec
o
m
m
e
n
d
at
io
n
s
d
es
p
it
e
d
a
t
a
l
im
i
tat
io
n
s
.
T
h
e
c
o
v
e
r
a
g
e
r
ate
i
m
p
r
o
v
e
m
e
n
t
co
n
ti
n
u
es
a
t
l
o
w
er
s
p
a
r
s
it
y
l
ev
els,
wi
th
HM
C
T
eCF
a
ch
ie
v
i
n
g
9
9
.
5
7
0
c
o
v
e
r
a
g
e
r
at
e
a
t
9
8
.
0
%
s
p
a
r
s
it
y
,
co
m
p
a
r
e
d
to
MC
-
T
eCF
’
s
9
8
.
4
6
0
,
s
h
o
w
in
g
a
c
o
n
s
is
t
en
t
ad
v
a
n
ta
g
e
i
n
r
ec
o
m
m
en
d
ati
o
n
co
m
p
r
e
h
e
n
s
i
v
e
n
ess
.
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.
3
6
,
No
.
3
,
Dec
em
b
er
20
24
:
1
9
1
9
-
1
9
2
8
1926
Fig
u
r
e
3
.
An
al
y
zin
g
MA
E
p
er
f
o
r
m
an
ce
ac
r
o
s
s
v
ar
io
u
s
s
p
ar
s
ity
lev
els
Fig
u
r
e
4
.
An
al
y
zin
g
c
o
v
er
a
g
e
r
ate
p
er
f
o
r
m
an
ce
ac
r
o
s
s
v
ar
io
u
s
s
p
ar
s
ity
lev
els
Ov
er
all,
th
e
HM
C
T
eCF
alg
o
r
i
th
m
d
em
o
n
s
tr
ated
s
u
p
er
io
r
p
e
r
f
o
r
m
a
n
ce
in
p
r
e
d
ictio
n
ac
c
u
r
ac
y
ac
r
o
s
s
m
u
ltip
le
d
atasets
an
d
ev
alu
ati
o
n
s
ce
n
ar
io
s
.
W
h
en
test
ed
o
n
th
e
R
estau
r
an
ts
d
ataset,
HM
C
T
eCF
ac
h
iev
ed
an
av
er
ag
e
MA
E
o
f
0
.
9
8
2
,
s
h
o
win
g
im
p
r
o
v
em
e
n
ts
o
f
4
-
1
6
%
o
v
er
b
en
c
h
m
ar
k
ap
p
r
o
ac
h
es.
T
h
e
alg
o
r
ith
m
’
s
ef
f
ec
tiv
en
ess
was
ev
en
m
o
r
e
ev
id
en
t
in
th
e
Ho
tels
d
ataset,
with
MA
E
im
p
r
o
v
em
en
ts
r
an
g
in
g
f
r
o
m
1
4
-
4
0
%
co
m
p
ar
ed
to
o
t
h
er
b
e
n
ch
m
ar
k
s
.
T
h
ese
r
esu
lts
wer
e
co
n
s
is
ten
t
ac
r
o
s
s
v
ar
io
u
s
s
izes
o
f
n
ea
r
est
n
eig
h
b
o
r
s
,
in
d
icatin
g
t
h
e
alg
o
r
ith
m
’
s
r
o
b
u
s
t
p
e
r
f
o
r
m
an
ce
in
d
if
f
er
en
t
r
ec
o
m
m
en
d
atio
n
c
o
n
tex
t
s
.
T
h
e
HM
C
T
eCF
ex
ce
lled
in
ad
d
r
ess
in
g
d
ata
s
p
ar
s
ity
,
a
co
m
m
o
n
is
s
u
e
in
r
e
co
m
m
en
d
e
r
s
y
s
tem
s
.
Acr
o
s
s
s
p
ar
s
ity
lev
els
f
r
o
m
9
9
.
8
%
to
9
8
.
0
%,
th
e
alg
o
r
ith
m
m
ain
tain
ed
th
e
lo
west
MA
E
v
alu
es
co
m
p
ar
e
d
to
b
e
n
ch
m
ar
k
s
.
At
th
e
h
ig
h
est
s
p
ar
s
ity
lev
el
o
f
9
9
.
8
%,
HM
C
T
eCF
ac
h
iev
ed
th
e
lo
west
MA
E
o
f
1
.
3
0
2
,
s
ig
n
if
ican
tly
o
u
tp
er
f
o
r
m
in
g
o
th
er
b
en
ch
m
ar
k
s
.
I
n
te
r
m
s
o
f
co
v
er
ag
e
r
ate,
HM
C
T
eCF
co
n
s
is
ten
tly
p
r
o
v
id
e
d
m
o
r
e
co
m
p
r
eh
e
n
s
iv
e
r
ec
o
m
m
en
d
atio
n
s
,
ac
h
iev
in
g
8
9
%
co
v
er
ag
e
at
9
9
.
8
%
s
p
ar
s
ity
,
f
ar
s
u
r
p
ass
in
g
o
th
er
b
e
n
c
h
m
ar
k
ap
p
r
o
ac
h
es.
T
h
is
co
n
s
is
ten
tly
s
u
p
er
io
r
p
er
f
o
r
m
an
ce
in
b
o
th
p
r
ed
ictio
n
a
cc
u
r
ac
y
a
n
d
co
v
e
r
ag
e
r
ate,
p
a
r
ticu
lar
ly
in
h
ig
h
-
s
p
ar
s
ity
s
ce
n
ar
io
s
,
u
n
d
er
s
co
r
e
s
HM
C
T
eCF
’
s
p
o
ten
tial
f
o
r
r
ea
l
-
wo
r
ld
ap
p
licatio
n
s
wh
er
e
d
ata
av
ailab
ilit
y
is
lim
ited
.
T
o
co
n
cl
u
d
e,
t
h
e
HM
C
T
eCF
alg
o
r
ith
m
r
ep
r
esen
ts
a
s
ig
n
if
ican
t
ad
v
an
ce
m
en
t
i
n
to
u
r
is
m
r
ec
o
m
m
en
d
er
s
y
s
tem
s
,
ef
f
ec
t
iv
ely
ad
d
r
ess
in
g
th
e
ch
allen
g
es
o
f
in
f
o
r
m
atio
n
o
v
er
l
o
ad
,
d
ata
s
p
ar
s
ity
,
an
d
d
iv
er
s
e
u
s
er
p
r
e
f
er
en
ce
s
.
B
y
in
teg
r
atin
g
tr
u
s
t
r
elatio
n
s
h
ip
s
an
d
m
u
lti
-
cr
iter
ia
r
atin
g
s
,
HM
C
T
eC
F
d
eliv
er
s
m
o
r
e
ac
cu
r
ate,
p
e
r
s
o
n
alize
d
,
an
d
r
eliab
le
r
ec
o
m
m
e
n
d
atio
n
s
,
p
av
in
g
th
e
way
f
o
r
en
h
a
n
ce
d
d
ec
is
io
n
-
m
ak
in
g
an
d
m
o
r
e
s
atis
f
y
in
g
tr
av
el
e
x
p
er
ien
ce
s
.
As
th
e
to
u
r
is
m
in
d
u
s
tr
y
ev
o
lv
es
with
in
th
e
d
ig
ital
lan
d
s
ca
p
e,
HM
C
T
eC
F
s
tan
d
s
o
u
t
as
a
p
r
o
m
is
in
g
s
o
lu
tio
n
,
o
f
f
er
in
g
s
ig
n
if
ican
t
b
en
ef
its
f
o
r
b
o
th
tr
av
e
ler
s
an
d
b
u
s
in
ess
es.
I
t
em
p
o
wer
s
tr
av
eler
s
b
y
d
eliv
er
in
g
tailo
r
ed
r
ec
o
m
m
e
n
d
atio
n
s
th
at
m
ee
t
th
eir
u
n
i
q
u
e
n
ee
d
s
,
t
h
er
eb
y
im
p
r
o
v
in
g
s
atis
f
ac
tio
n
an
d
en
g
ag
em
en
t.
Fo
r
b
u
s
in
ess
es,
th
e
alg
o
r
ith
m
p
r
o
v
id
es
a
to
o
l
t
o
b
etter
u
n
d
er
s
tan
d
an
d
ca
ter
to
c
u
s
to
m
er
p
r
ef
er
e
n
ce
s
,
p
o
ten
tially
in
cr
ea
s
in
g
l
o
y
alty
an
d
r
e
v
en
u
e.
4.
CO
NCLU
SI
O
N
I
n
th
e
er
a
o
f
in
f
o
r
m
atio
n
ab
u
n
d
an
ce
,
wh
er
e
o
n
lin
e
r
eso
u
r
ce
s
r
elate
d
to
tr
av
el
an
d
to
u
r
is
m
ar
e
p
r
o
life
r
atin
g
at
an
u
n
p
r
ec
e
d
e
n
ted
r
ate,
ad
v
a
n
ce
d
to
o
ls
ar
e
im
p
er
ativ
e
to
ass
is
t
u
s
er
s
in
n
av
ig
atin
g
th
is
v
ast
lan
d
s
ca
p
e
an
d
m
a
k
in
g
well
-
i
n
f
o
r
m
e
d
d
ec
is
io
n
s
.
T
h
is
s
tu
d
y
in
tr
o
d
u
ce
s
th
e
HM
C
T
eCF
alg
o
r
ith
m
,
a
n
o
v
el
ap
p
r
o
ac
h
d
esig
n
ed
t
o
en
h
a
n
ce
th
e
ef
f
ec
tiv
en
ess
o
f
r
e
co
m
m
en
d
e
r
s
y
s
tem
s
in
t
h
e
to
u
r
is
m
d
o
m
ain
.
B
y
s
ea
m
less
ly
in
teg
r
atin
g
m
u
lti
-
cr
iter
ia
r
atin
g
s
a
n
d
t
r
u
s
t
-
b
ased
m
ec
h
a
n
is
m
s
,
HM
C
T
eC
F
o
f
f
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I
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2
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52
In
d
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n
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J
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p
Sci
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Vo
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3
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3
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Dec
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b
er
20
24
:
1
9
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1928
B
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RAP
H
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S O
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AUTH
O
RS
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y
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m
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iv
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rsity
,
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o
rd
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n
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se
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terin
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sh
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m
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.
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t
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m
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n
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iv
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se
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S
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n
d
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rit
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c
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n
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c
o
n
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ted
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t
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m
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il
:
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.
a
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a
id
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h
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m
m
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n
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.
e
d
u
.
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.
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sle
h
M
.
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a
lh
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j
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se
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tu
re
r
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t
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-
A
h
li
y
y
a
Am
m
a
n
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i
v
e
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.
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re
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h
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ter
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e
fro
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d
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l
p
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ia
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iv
e
rsity
,
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r
d
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n
,
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,
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is
m
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ste
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d
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re
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m
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ter
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m
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n
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c
e
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rd
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n
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n
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n
d
h
is
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h
.
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in
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u
lt
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rk
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ro
to
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o
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o
m
Un
i
v
e
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a
i
n
s
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lay
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0
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1
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se
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rc
h
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r
e
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o
f
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s
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IP
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u
lt
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rk
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n
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,
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n
d
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n
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o
n
c
o
n
tr
o
l.
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c
a
n
b
e
c
o
n
tac
ted
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t
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m
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il
:
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.
a
b
u
a
lh
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j@a
m
m
a
n
u
.
e
d
u
.
jo
.
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a
d
Adel
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-
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h
a
r
e
h
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re
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e
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e
d
h
is
first
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e
g
re
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n
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m
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ter
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c
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e
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m
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Al
-
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y
t
Un
iv
e
rsity
,
J
o
rd
a
n
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i
n
2
0
0
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,
M
a
ste
r
d
e
g
re
e
fro
m
Un
iv
e
rsiti
S
a
in
s
M
a
lay
sia
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),
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a
lay
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,
in
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0
0
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,
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n
d
h
is
P
h
.
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d
e
g
re
e
fro
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USM
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lay
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,
in
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0
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2
.
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se
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rc
h
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se
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n
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n
d
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lt
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ia
se
c
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rit
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.
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in
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e
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a
ted
m
a
n
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h
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s
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n
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ield
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c
h
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s
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rk
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c
ti
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n
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n
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tr
a
c
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n
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c
a
n
b
e
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ted
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.
a
b
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sh
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re
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a
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m
m
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n
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e
d
u
.
j
o
.
Evaluation Warning : The document was created with Spire.PDF for Python.