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Sci,
Vo
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13
,
No
.
1
,
J
an
u
ar
y
2
0
1
9
:
41
–
47
42
d
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r
o
d
u
cin
g
r
ar
e
ite
m
s
f
r
o
m
v
ar
io
u
s
d
ata
b
as
es.
I
n
th
i
s
s
tu
d
y
,
t
w
o
co
r
e
g
litc
h
es
w
it
h
cu
r
r
e
n
t
m
et
h
o
d
s
w
er
e
p
r
o
j
ec
te
d
.
E
x
ca
v
at
in
g
p
r
o
g
r
ess
io
n
is
b
ei
n
g
p
r
ep
ar
ed
w
it
h
s
ta
ti
s
tical
m
e
th
o
d
s
lik
e
P
o
is
s
o
n
d
is
tr
ib
u
tio
n
.
Kir
an
a
n
d
R
e
[
9
]
a
n
ticip
ate
d
a
b
etter
m
u
ltip
le
m
i
n
i
m
u
m
-
s
u
p
p
o
r
t
m
et
h
o
d
f
o
r
m
in
i
n
g
t
h
e
r
ar
e
ass
o
ciatio
n
r
u
le
s
.
T
h
eir
m
et
h
o
d
n
ee
d
s
s
p
ec
if
y
i
n
g
m
u
ltip
le
m
in
i
m
u
m
s
u
p
p
o
r
t,
w
h
ic
h
is
p
r
o
b
le
m
atic
r
elate
d
to
a
s
i
n
g
le
m
in
i
m
u
m
ad
j
u
s
ted
s
u
p
p
o
r
t.
Srik
an
t
an
d
Ag
r
a
w
ali
n
1
9
9
7
p
r
o
d
u
ce
d
a
s
m
all
al
t
er
atio
n
o
f
cla
s
s
ica
l
alg
o
r
ith
m
.
I
n
t
h
i
s
s
tu
d
y
,
t
h
e
r
a
r
e
ite
m
s
ar
e
m
o
r
eo
v
er
co
m
p
o
s
ed
o
n
t
h
e
b
asi
s
o
f
m
i
n
i
m
u
m
s
u
p
p
o
r
t
v
al
u
e.
Sti
ll,
it f
lo
p
s
to
ca
tch
all
t
h
e
r
ar
e
item
s
et
s
.
Sev
er
al
i
n
v
e
s
ti
g
ato
r
s
h
av
e
ap
p
lied
ass
o
ciatio
n
r
u
les
f
o
r
d
iab
etic
p
atien
ts
.
P
ir
i
et
al
[
1
0
]
an
al
y
s
ed
th
e
d
ata
o
f
2
3
,
1
7
,
2
5
9
p
atien
ts
id
en
tifie
d
w
it
h
h
y
p
er
ten
s
io
n
a
n
d
d
iab
etes.
B
y
p
u
t
o
n
as
s
o
ciatio
n
an
al
y
s
i
s
,
th
e
y
in
itiate
h
y
p
er
ten
s
io
n
an
d
d
iab
etes
w
a
s
to
u
g
h
l
y
co
n
n
ec
ted
.
Mu
s
ta
f
a
e
t
al
[
1
1
]
ex
p
lo
r
ed
v
ar
io
u
s
al
g
o
r
ith
m
s
f
o
r
g
en
er
ati
n
g
as
s
o
ciatio
n
r
u
les.
T
h
ey
a
n
al
y
s
ed
t
h
e
alg
o
r
it
h
m
s
o
n
b
en
c
h
m
ar
k
d
en
s
e
d
atas
ets
an
d
f
o
u
n
d
FP
-
Gr
o
w
t
h
al
g
o
r
ith
m
i
s
b
etter
as
co
m
p
ar
ed
to
o
th
er
s
.
P
r
asad
[
1
2
]
d
esig
n
ed
a
n
e
w
al
g
o
r
ith
m
w
h
o
s
e
ai
m
w
a
s
to
eli
m
i
n
ate
lo
w
-
p
r
o
f
it
ite
m
s
ets.
T
h
e
alg
o
r
ith
m
u
s
es
s
h
o
r
t
tim
e
f
o
r
g
en
er
ati
n
g
h
ig
h
-
p
r
o
f
it
ite
m
s
ets.
B
u
t
th
e
li
m
ita
tio
n
i
s
t
h
at
i
t is
u
n
ab
le
to
g
e
n
er
ate
r
ar
e
ite
m
s
ets
an
d
m
a
y
b
e
ex
ten
d
ed
f
o
r
b
ig
d
ataset
s
.
Hu
s
s
ai
n
et
al
[
1
3
]
u
s
ed
A
p
r
io
r
i
alg
o
r
it
h
m
f
o
r
g
e
n
er
ati
n
g
a
s
s
o
ciatio
n
r
u
le
s
a
n
d
an
al
y
s
ed
t
h
e
ac
ad
e
m
ic
p
er
f
o
r
m
an
ce
o
f
s
tu
d
e
n
ts
u
s
i
n
g
W
E
KA
.
T
o
in
cr
ea
s
e
th
e
q
u
alit
y
o
f
d
r
aw
i
n
g
o
u
t
r
ar
e
ite
m
s
,
a
tec
h
n
iq
u
e
n
a
m
ed
“
M
u
ltip
le
Mi
n
i
m
u
m
S
u
p
p
o
r
t
Mo
d
el”
w
a
s
d
e
v
elo
p
ed
b
y
D
ar
r
ab
et
al
[
1
4
]
.
E
v
er
y
ite
m
i
s
allo
ca
ted
alo
n
g
w
it
h
a
lea
s
t
s
u
p
p
o
r
t
co
s
t
ca
lled
“
Mi
n
i
m
u
m
I
te
m
S
u
p
p
o
r
t”
(
MI
S)
in
th
i
s
m
et
h
o
d
.
T
h
is
v
al
u
e
i
s
allo
ca
ted
to
e
v
er
y
ite
m
id
en
t
ical
to
a
s
ec
t
io
n
o
f
its
s
u
p
p
o
r
t.
T
h
e
ap
p
r
o
ac
h
,
d
escr
ib
es
th
e
least
s
u
p
p
o
r
t
o
f
a
r
ar
e
r
u
le
in
r
elatio
n
s
o
f
m
i
n
i
m
u
m
i
te
m
s
u
p
p
o
r
t
o
f
th
e
ite
m
s
t
h
at
lo
o
k
in
t
h
e
r
u
l
e.
i.e
.
ev
er
y
ite
m
i
n
th
e
d
ata
b
ase
ca
n
h
av
e
a
leas
t
ite
m
s
u
p
p
o
r
t
th
at
ca
n
b
e
co
n
s
id
er
ed
b
y
m
ea
n
s
o
f
s
o
m
e
m
et
h
o
d
o
r
ca
n
b
e
q
u
an
tif
ie
d
b
y
th
e
u
s
er
.
B
y
g
i
v
i
n
g
v
ar
i
o
u
s
MI
S
v
alu
e
s
f
o
r
v
ar
io
u
s
ite
m
s
,
th
e
u
s
er
p
o
s
iti
v
el
y
s
tates
d
if
f
er
en
t
r
u
le
s
.
T
h
is
alg
o
r
it
h
m
u
s
ed
t
h
e
d
o
w
n
w
ar
d
clo
s
u
r
e
p
r
o
p
er
ty
.
A
cc
o
r
d
in
g
to
th
is
p
r
o
p
er
ty
,
e
v
er
y
s
u
b
s
et
o
f
f
r
eq
u
en
t
ite
m
s
et
is
f
r
eq
u
en
t.
I
f
w
e
u
s
e
t
h
is
p
r
o
p
er
ty
,
v
ar
io
u
s
in
ter
esti
n
g
ite
m
s
m
a
y
b
e
i
g
n
o
r
ed
o
r
d
is
ca
r
d
ed
.
A
lter
n
ati
v
e
m
et
h
o
d
o
lo
g
y
f
o
r
p
r
o
d
u
cin
g
r
ar
e
p
a
tter
n
ar
e
r
elativ
e
s
u
p
p
o
r
t
A
p
r
io
r
i
al
g
o
r
ith
m
(
R
S
AA)
p
r
o
p
o
s
ed
b
y
E
lah
e
et
a
l
[
1
5
]
.
T
h
is
al
g
o
r
ith
m
u
s
es
th
r
ee
c
u
s
to
m
er
s
tated
s
u
p
p
o
r
ts
k
n
o
wn
a
s
Fir
s
t
s
u
p
p
o
r
t,
Seco
n
d
s
u
p
p
o
r
t
an
d
R
elat
iv
e
s
u
p
p
o
r
t.
I
f
s
u
p
p
o
r
t
v
al
u
e
o
f
a
n
y
i
te
m
i
s
s
u
p
er
io
r
th
an
o
r
eq
u
al
to
f
ir
s
t
s
u
p
p
o
r
t
v
alu
e,
it
is
ca
lled
f
r
eq
u
en
t
i
te
m
.
I
f
s
u
p
p
o
r
t
v
alu
e
o
f
an
ite
m
is
s
m
aller
th
a
n
f
ir
s
t
s
u
p
p
o
r
t
v
alu
e
b
u
t
lar
g
er
th
a
n
o
r
eq
u
al
to
s
ec
o
n
d
s
u
p
p
o
r
t
v
alu
e,
it
is
ca
lled
r
ar
e
ite
m
;
it
e
m
s
et
s
h
a
v
in
g
r
ar
e
ite
m
s
h
a
v
e
to
m
o
lli
f
y
2
n
d
s
u
p
p
o
r
t a
n
d
its
r
elativ
e
s
u
p
p
o
r
t sh
o
u
ld
f
u
lf
il lo
w
est r
elati
v
e
s
u
p
p
o
r
t id
en
tif
ied
b
y
t
h
e
u
s
er
.
B
h
att
et
al
[
1
6
]
p
r
o
p
o
s
ed
an
ex
ten
s
io
n
o
f
R
P
-
T
r
ee
alg
o
r
ith
m
ca
lled
a
s
Ma
x
i
m
u
m
C
o
n
s
tr
ain
t
R
ar
e
P
atter
n
T
r
ee
A
lg
o
r
it
h
m
.
T
h
is
alg
o
r
ith
m
tak
e
s
t
h
e
tr
a
n
s
ac
tio
n
al
d
ata
s
et.
W
it
h
a
p
r
e
v
io
u
s
MI
S
Val
u
e
o
f
ite
m
,
th
is
tech
n
iq
u
e
co
n
tr
o
ls
th
e
r
ar
e
ite
m
s
et
f
r
o
m
th
e
d
at
a
s
et.
T
h
is
tr
ee
ch
o
o
s
e
s
t
h
e
tr
an
s
ac
tio
n
s
o
f
s
in
g
le
r
ar
e
ite
m
s
et
i
n
it.
T
h
e
m
et
h
o
d
o
lo
g
y
f
i
n
d
s
o
n
l
y
r
ar
e
ite
m
s
a
n
d
cu
ts
t
h
e
o
th
er
ite
m
s
et
f
r
o
m
t
h
e
tr
an
s
ac
tio
n
at
t
h
e
ti
m
e
o
f
tr
ee
co
n
s
tr
u
ctio
n
.
T
h
is
tr
ee
is
t
h
e
ex
te
n
s
io
n
o
f
R
P
-
T
r
ee
W
h
ile
m
in
in
g
t
h
e
r
ar
e
it
e
m
s
ets,
t
h
is
a
lg
o
r
it
h
m
u
s
e
s
tr
ee
g
en
er
atio
n
.
A
s
a
n
in
s
er
tio
n
o
f
a
n
o
d
e
in
t
h
e
tr
ee
g
e
n
er
atio
n
,
th
e
p
r
o
ce
s
s
m
a
y
b
e
ex
p
en
s
i
v
e.
1
.
2
.
T
he
P
ro
ble
m
I
n
w
h
o
lesale
p
r
o
d
u
ctio
n
[
1
7
]
,
th
e
m
ar
k
et
-
b
ask
e
t
s
t
u
d
y
is
w
i
s
h
ed
f
o
r
d
eter
m
in
i
n
g
w
h
ic
h
t
h
i
n
g
s
ar
e
to
b
e
b
o
u
g
h
t
to
g
et
h
er
s
o
as
to
k
e
ep
b
u
y
i
n
g
b
e
h
av
io
u
r
o
f
co
n
s
u
m
er
s
.
I
n
m
ar
k
et
-
b
a
s
k
et
s
t
u
d
y
,
s
o
m
e
co
llectio
n
s
o
f
th
i
n
g
s
,
s
u
c
h
as
to
o
t
h
p
aste
a
n
d
to
o
th
b
r
u
s
h
,
h
ap
p
e
n
co
m
m
o
n
l
y
.
W
h
e
n
as
s
o
ciate
d
to
m
i
lk
&
b
r
ea
d
,
s
o
m
e
t
h
i
n
g
s
lik
e
a
ch
ai
n
&
a
g
o
ld
r
in
g
ar
e
r
ar
ely
r
elate
d
ite
m
s
ets,
b
u
t
r
ef
lecte
d
to
b
e
a
s
ig
n
i
f
ica
n
t
r
el
atio
n
s
h
ip
.
W
e
m
a
y
also
d
is
co
v
er
s
o
m
e
in
f
r
eq
u
en
t
r
elatio
n
s
th
at
w
e
ca
n
n
o
t
v
is
u
alis
e.
T
h
e
p
r
o
b
lem
o
f
d
eter
m
i
n
in
g
r
ar
e
ite
m
s
h
a
s
j
u
s
t c
au
g
h
t t
h
e
atte
n
tio
n
o
f
th
e
d
ata
m
i
n
i
n
g
.
Sin
g
le
m
i
n
i
m
u
m
co
n
s
tr
ai
n
t
m
o
d
el
ad
o
p
ts
th
at
all
ite
m
s
h
a
v
e
an
alo
g
o
u
s
o
cc
u
r
r
en
ce
i
n
t
h
e
d
ata
s
et.
I
n
s
ev
er
al
ex
is
te
n
t a
p
p
licatio
n
s
,
w
e
w
i
ll e
n
co
u
n
ter
f
o
llo
w
in
g
g
litch
e
s
[
1
8
]
:
a)
I
f
th
e
least
s
u
p
p
o
r
t
is
f
ix
ed
t
o
a
u
p
p
er
v
alu
e,
w
e
ar
e
u
n
ab
le
to
ca
tch
th
e
r
u
les
th
a
t
co
n
t
ain
o
f
r
ar
e
ite
m
s
e
ts
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
Desig
n
a
n
d
d
ev
elo
p
men
t
o
f a
n
a
lg
o
r
ith
m
fo
r
min
in
g
r
a
r
e
itemsets
(
S
a
ch
in
S
h
a
r
ma
)
43
b)
Fo
r
f
in
d
i
n
g
b
o
th
r
ar
e
an
d
f
r
e
q
u
en
t
ite
m
s
,
it
i
s
n
ec
e
s
s
ar
y
t
o
f
ix
litt
le
s
m
alles
t
s
u
p
p
o
r
t
v
alu
e
b
u
t
it
m
ak
e
s
a
b
ig
q
u
a
n
tit
y
o
f
co
m
m
o
n
ar
r
an
g
e
m
en
ts
w
h
ic
h
ar
e
n
o
t v
alu
ed
.
R
ar
e
ite
m
s
ca
n
b
e
u
s
ed
in
s
e
v
er
al
ar
ea
s
lik
e
te
x
t
e
x
ca
v
at
i
n
g
-
i
n
d
ir
ec
t
r
elatio
n
s
ca
n
u
s
ed
to
ca
tch
s
u
b
s
t
itu
te
s
,
an
to
n
y
m
t
h
at
is
u
s
ed
in
d
if
f
er
e
n
t si
tu
at
io
n
s
.
I
n
f
r
e
q
u
en
t p
atter
n
s
ca
n
b
e
u
s
ed
to
id
en
tify
er
r
o
r
s
.
I
n
f
r
eq
u
e
n
t ite
m
s
et
h
as
s
ig
n
i
f
i
ca
n
t p
r
ac
tice
in
[
1
9
]
:
(
i)
R
e
m
o
v
a
l
o
f
u
n
d
esira
b
le
ass
o
ciatio
n
r
u
les
f
r
o
m
r
ar
e
ite
m
s
e
ts
(
ii)
n
u
m
er
ical
d
i
s
cl
o
s
u
r
e
r
is
k
v
alu
a
tio
n
w
h
er
e
r
ar
e
p
atter
n
s
in
u
n
id
en
ti
f
ied
s
u
r
v
e
y
d
ata
ca
n
lead
to
s
tatis
tical
r
ev
elat
io
n
(
iii)
s
ca
m
d
is
co
v
er
y
w
h
er
e
r
ar
e
p
atter
n
s
i
n
m
o
n
eta
r
y
d
ata
m
a
y
p
r
o
p
o
s
e
u
n
co
m
m
o
n
ac
tiv
it
y
r
elate
d
w
it
h
f
ak
e
b
eh
av
io
u
r
(
i
v
)
B
io
-
in
f
o
r
m
atic
s
w
h
er
e
r
ar
e
p
atte
r
n
s
i
n
m
icr
o
ar
r
ay
d
ata
m
a
y
p
r
o
p
o
s
e
g
en
o
m
ic
d
i
s
ar
r
a
y
s
.
R
ar
e
i
te
m
s
ca
r
r
y
ex
tr
e
m
e
l
y
s
ti
m
u
la
tin
g
i
n
f
o
r
m
a
tio
n
to
s
ev
er
al
s
p
h
er
es
w
it
h
m
ed
icatio
n
o
r
n
at
u
r
al
s
cie
n
ce
.
1
.
3
.
P
ro
po
s
ed
So
lutio
n
I
n
th
is
p
ap
er
,
th
e
au
t
h
o
r
w
ill
d
esig
n
a
n
e
w
a
lg
o
r
it
h
m
/
tec
h
n
iq
u
e
w
h
o
s
e
p
u
r
p
o
s
e
is
to
m
i
n
e
r
ar
e
ite
m
s
ets
f
r
o
m
t
h
e
tr
an
s
ac
tio
n
a
l d
atab
ase.
T
h
is
m
e
th
o
d
w
ill al
s
o
o
v
er
co
m
e
li
m
itatio
n
s
o
f
e
x
i
s
tin
g
ap
p
r
o
ac
h
.
a)
A
p
r
io
r
i
-
R
ar
e,
A
p
r
io
r
i
-
I
n
v
er
s
e
is
n
o
t a
b
le
to
f
i
n
d
r
ar
e
ite
m
s
et
s
.
b)
AR
I
M
A
Alg
o
r
it
h
m
i
s
ab
le
t
o
g
en
er
ate
r
ar
e
ite
m
s
et
b
u
t
th
e
r
u
le
s
p
r
o
d
u
ce
d
f
r
o
m
t
h
e
m
ar
e
n
o
t
a
ll
s
ti
m
u
la
tin
g
.
c)
T
h
e
p
r
o
ce
s
s
m
a
y
b
e
e
x
p
en
s
iv
e
as th
e
ex
is
ti
n
g
alg
o
r
it
h
m
u
s
e
s
tr
ee
g
en
er
atio
n
m
et
h
o
d
.
d)
Var
io
u
s
R
ar
e
ite
m
s
e
ts
m
a
y
b
e
ig
n
o
r
ed
o
r
d
is
ca
r
d
ed
b
y
u
s
i
n
g
d
o
w
n
w
ar
d
clo
s
u
r
e
p
r
o
p
er
ty
.
T
h
e
o
r
g
an
izatio
n
o
f
t
h
e
r
esear
ch
p
ap
er
is
as
f
o
llo
w
:
I
n
s
ec
ti
o
n
2
,
p
r
o
p
o
s
ed
alg
o
r
ith
m
i
s
o
f
f
er
ed
an
d
I
n
v
e
s
tig
a
tio
n
al
r
es
u
lt
s
ar
e
s
h
o
w
n
i
n
s
ec
tio
n
3
.
C
o
n
clu
s
io
n
p
ar
t is g
i
v
en
i
n
s
ec
t
io
n
4
.
2.
P
RO
P
O
SE
D
M
E
T
H
O
D
Af
ter
r
ev
ie
w
i
n
g
an
d
an
a
l
y
s
i
n
g
th
e
v
ar
io
u
s
al
g
o
r
ith
m
s
,
it
i
s
p
er
ce
iv
ed
th
at
al
g
o
r
ith
m
s
m
en
tio
n
ed
ab
o
v
e
h
av
e
s
o
m
e
d
r
a
w
b
ac
k
s
.
T
h
e
ex
is
ti
n
g
al
g
o
r
ith
m
s
A
p
r
io
r
i
-
ra
r
e,
A
p
r
io
r
i
-
in
v
er
s
e
ar
e
n
o
t
ab
le
to
f
i
n
d
all
r
ar
e
ite
m
s
et
s
.
W
h
i
le
t
h
e
ex
i
s
t
in
g
m
e
th
o
d
/
p
r
o
ce
d
u
r
e
AR
I
M
A
i
s
ab
le
to
g
en
er
ate
r
ar
e
ite
m
s
e
t.
A
ls
o
,
t
h
e
r
u
le
s
p
r
o
d
u
ce
d
f
r
o
m
th
e
m
ar
e
n
o
t
a
ll
s
ti
m
u
lati
n
g
.
T
o
r
em
o
v
e
th
e
d
r
a
w
b
ac
k
s
m
e
t
b
y
th
e
a
ll
m
et
h
o
d
s
,
w
e
s
u
g
g
e
s
t
a
n
e
w
ap
p
r
o
ac
h
w
h
ic
h
f
o
llo
w
s
a
b
id
ir
ec
tio
n
al
ap
p
r
o
ac
h
.
T
h
e
n
e
w
m
e
th
o
d
u
s
e
s
th
e
d
at
aset
a
nd
m
i
n
i
m
u
m
th
r
es
h
o
ld
as
i
n
p
u
t
an
d
y
ield
s
r
ar
e
ite
m
s
ets
a
s
o
u
tp
u
t.
I
t
h
elp
s
in
p
r
u
n
in
g
t
h
e
ca
n
d
id
ate.
T
h
e
s
tep
s
o
f
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
ar
e
as f
o
llo
w
:
2
.
1
.
Ste
ps
:
a)
Scan
t
h
e
d
atab
ase
o
n
l
y
o
n
e
ti
m
e
to
ca
tch
r
ea
l s
u
p
p
o
r
t o
f
item
s
.
b)
I
te
m
s
i
n
th
e
tr
a
n
s
ac
t
io
n
ar
e
in
ascen
d
i
n
g
/
d
esce
n
d
i
n
g
o
r
d
er
ac
co
r
d
in
g
to
m
u
ltip
le
s
u
p
p
o
r
t
th
r
esh
o
ld
s
.
c)
C
alcu
late
MI
S v
al
u
e
f
o
r
ea
ch
i
te
m
i
n
tr
an
s
ac
tio
n
d
ata
s
et.
MI
S =
ß
S(ij
)
if
ß
S(i
j
)
>
L
S
S (
i
j
)
else
W
h
er
e
ß
is
a
u
s
er
d
ef
in
ed
v
al
u
e
lie
s
b
et
w
ee
n
ze
r
o
an
d
o
n
e;
S
(
ij
)
d
en
o
tes
th
ep
er
ce
n
ta
g
e
s
u
p
p
o
r
t
o
f
an
y
ite
m
eq
u
a
l to
f
(
ij
)
/ N
*
1
0
0
; a
n
d
L
S i
s
u
s
er
d
ef
in
ed
least
s
u
p
p
o
r
t v
alu
e.
d)
Fin
d
t
h
e
least
m
i
n
i
m
u
m
s
u
p
p
o
r
t th
r
esh
o
ld
.
e)
Fin
d
r
ar
e
ite
m
s
et
i
f
s
u
p
p
o
r
t
is
le
s
s
th
a
n
L
S
an
d
lar
g
er
t
h
an
o
r
eq
u
al
to
lea
s
t
m
i
n
i
m
u
m
s
u
p
p
o
r
t
th
r
es
h
o
ld
.
f)
Fin
d
t
h
e
tr
an
s
ac
t
io
n
h
a
v
i
n
g
atl
ea
s
t o
n
e
r
ar
e
ite
m
s
et
f
r
o
m
tr
a
n
s
ac
tio
n
d
ata
s
et.
2
.
2
.
F
lo
w
Cha
rt
Fo
llo
w
i
n
g
is
t
h
e
d
escr
ip
tio
n
p
r
o
v
id
ed
f
o
r
Giv
en
a
tr
a
n
s
ac
tio
n
d
atab
ase
DB
as sh
o
w
n
in
Fi
g
u
r
e
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
13
,
No
.
1
,
J
an
u
ar
y
2
0
1
9
:
41
–
47
44
Fig
u
r
e
1
.
Giv
en
a
tr
a
n
s
ac
tio
n
d
atab
ase
DB
as sh
o
w
n
E
x
a
m
p
le:
Giv
e
n
a
tr
a
n
s
ac
tio
n
d
atab
ase
DB
as
s
h
o
w
n
i
n
th
e
T
ab
le
1
w
it
h
Mi
n
i
m
u
m
S
u
p
p
o
r
t
(
L
S)
f
i
x
ed
at
2
0
% a
n
d
ß
=0
.
7
;
th
e
m
u
ltip
le
ite
m
s
u
p
p
o
r
ts
o
f
ite
m
s
i
n
T
ab
le
2
.
T
ab
le
1
.
T
r
an
s
ac
tio
n
s
C
o
n
tain
in
g
Var
io
u
s
I
te
m
s
TI
D
I
t
e
ms
T1
D
,
C
,
A
,
F
T2
G
,
C
,
A
,
F
,
E
T3
B
,
A
,
C
,
F
,
H
T4
G
,
B
,
F
T5
B,C
T
ab
le
2
.
C
alcu
latio
n
o
f
Su
p
p
o
r
t
%ag
e
I
t
e
ms
A
B
C
D
E
F
G
H
M
I
S
42
42
56
20
20
56
28
20
S
u
p
p
o
r
t
%a
g
e
60
60
80
20
20
80
40
20
As
p
er
th
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
,
th
e
ac
tu
a
l
s
u
p
p
o
r
tp
er
ce
n
tag
e
an
d
m
i
n
i
m
u
m
s
u
p
p
o
r
t
th
r
esh
o
ld
v
alu
es
o
f
v
ar
io
u
s
ite
m
s
ca
lc
u
lated
ar
e
s
h
o
w
n
in
T
ab
le
1
.
MI
S
v
alu
e
s
ar
e
ca
lcu
lated
ac
co
r
d
i
n
g
to
th
e
f
o
r
m
u
l
a
d
escr
ib
ed
in
s
tep
2
o
f
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
.
No
tice,
if
ß
=1
an
d
Sij
≥
L
S,
m
in
i
m
u
m
s
u
p
p
o
r
t
th
r
es
h
o
ld
v
alu
e
o
f
an
y
ite
m
ar
e
th
e
r
ea
l
s
u
p
p
o
r
t
o
f
ite
m
s
Sij
,
w
h
er
ea
s
i
f
ß
=0
,
th
er
e
is
o
n
l
y
s
i
n
g
le
m
in
i
m
u
m
s
u
p
p
o
r
t.
I
t
is
to
b
e
n
o
ted
th
at
ß
p
ar
am
eter
is
d
et
er
m
in
ed
b
y
t
h
e
f
o
r
m
u
la[
9
]
:
.
I
n
T
ab
le
2
,
th
e
r
esu
lts
ar
e
ar
r
an
g
ed
an
d
s
to
r
ed
ac
co
r
d
in
g
to
Min
i
m
u
m
Su
p
p
o
r
t T
h
r
esh
o
ld
v
alu
es.
L
ea
s
t
m
i
n
i
m
u
m
s
u
p
p
o
r
t
th
r
es
h
o
ld
v
al
u
e
is
2
0
.
D,
E
,
H
ar
e
r
ar
e
item
s
ets
a
s
th
e
s
e
ite
m
s
ar
e
n
o
t
s
m
al
ler
t
h
an
least
s
u
p
p
o
r
t
v
al
u
e
b
u
t
lar
g
er
th
a
n
o
r
eq
u
al
to
s
m
al
lest
m
in
i
m
u
m
t
h
r
es
h
o
ld
v
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le
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e
t.
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s
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n
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T
ab
le
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T
a
b
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3
,
th
e
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su
lt
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g
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m
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n
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a
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i
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m
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3
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A
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esh
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--
C
F
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B
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56
56
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42
28
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60
60
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Evaluation Warning : The document was created with Spire.PDF for Python.
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n
d
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n
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n
J
E
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E
n
g
&
C
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m
p
Sci
I
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N:
2502
-
4752
Desig
n
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n
d
d
ev
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men
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lg
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T
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3.
RE
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D
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x
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1
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
Desig
n
a
n
d
d
ev
elo
p
men
t
o
f a
n
a
lg
o
r
ith
m
fo
r
min
in
g
r
a
r
e
itemsets
(
S
a
ch
in
S
h
a
r
ma
)
47
Fro
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t
h
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x
p
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m
e
n
tal
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lts
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it i
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r
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g
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lt a
s
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ith
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C
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f
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d
s
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r
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k
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ets t
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t i
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ee
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m
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a
m
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t o
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ti
m
e
a
n
d
s
a
m
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m
b
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d
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lik
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A
p
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io
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i.
4.
CO
NCLU
SI
O
N
As
s
i
n
g
le
m
i
n
i
m
u
m
s
u
p
p
o
r
t
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i
n
ad
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ate
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o
r
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o
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g
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n
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en
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if
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s
o
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th
e
d
if
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er
en
t
ite
m
s
i
n
th
e
d
atab
ase.
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n
r
ea
lis
tic
ap
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c
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d
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ca
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t
is
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p
tab
le
to
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e
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m
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g
e,
n
o
r
it
is
ap
p
r
o
p
r
iate
to
s
et
it
to
o
s
m
all.
I
n
t
h
i
s
p
ap
er
,
w
e
h
a
v
e
ex
p
lo
r
ed
th
e
p
r
o
b
le
m
o
f
u
s
i
n
g
i
te
m
s
p
ec
if
ic
m
in
i
m
u
m
s
u
p
p
o
r
t.
I
t p
e
r
m
i
ts
t
h
e
cu
s
to
m
er
to
s
tip
u
late
m
u
ltip
le
m
i
n
i
m
u
m
i
te
m
.
T
o
an
s
w
er
th
i
s
p
r
o
b
lem
,
w
e
h
a
v
e
p
r
o
p
o
s
ed
an
al
g
o
r
ith
m
w
h
ic
h
is
s
k
il
f
u
l
o
f
d
r
a
w
i
n
g
o
u
t
r
ar
e
p
atter
n
s
e
f
f
icie
n
tl
y
.
W
e
h
av
e
ass
es
s
ed
t
h
e
p
er
f
o
r
m
a
n
ce
o
f
p
r
o
p
o
s
ed
alg
o
r
ith
m
b
y
s
h
o
w
in
g
a
test
o
n
v
ar
io
u
s
d
atasets
.
T
h
e
ab
o
v
e
m
e
n
tio
n
e
d
r
esu
lt
s
s
h
o
w
t
h
at
p
r
o
p
o
s
ed
alg
o
r
ith
m
h
as
co
m
e
o
u
t
f
r
o
m
th
e
r
ar
e
ite
m
p
r
o
b
lem
a
n
d
g
i
v
es
u
s
er
m
o
r
e
f
lex
ib
le
an
d
d
o
m
i
n
an
t
m
o
d
el
to
s
tat
e
m
i
n
i
m
u
m
s
u
p
p
o
r
t
f
o
r
r
ar
e
ite
m
.
T
h
u
s
,
p
r
o
p
o
s
ed
alg
o
r
ith
m
allo
w
s
u
s
to
co
llier
y
r
ar
e
p
atter
n
w
it
h
o
u
t
cr
ea
tin
g
an
y
u
n
e
x
citi
n
g
a
n
d
ted
io
u
s
p
atter
n
.
RE
F
E
R
E
NC
E
S
[1
]
T
ro
ian
o
,
S
c
i
b
e
ll
i,
Birt
o
lo
.
“
A
f
a
st
a
lg
o
rit
h
m
f
o
r
m
in
in
g
ra
re
it
e
m
s
e
ts
”
.
Pro
c
e
e
d
in
g
s
o
f
Ni
n
t
h
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
In
tell
ig
e
n
t
S
y
ste
ms
De
sig
n
a
n
d
Ap
p
li
c
a
ti
o
n
s
,
2
0
0
9
:
1
1
4
9
-
55
.
[2
]
L
iu
,
Hs
u
,
M
a
,
“
M
in
i
n
g
a
ss
o
c
ia
ti
o
n
r
u
les
w
it
h
m
u
lt
ip
le
m
in
imu
m
su
p
p
o
rts
”
.
Pro
c
e
e
d
in
g
s
o
f
ACM
S
IGKD
D
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
K
n
o
wled
g
e
d
isc
o
v
e
ry
a
n
d
d
a
ta
mi
n
in
g
,
1
9
9
9
:
3
3
7
-
3
4
1
.
[3
]
L
a
s
z
lo
S
z
a
th
m
a
r
y
,
Am
e
d
e
o
Na
p
o
li
,
P
e
tk
o
V
a
lt
c
h
e
v
.
“
T
o
w
a
rd
s
Ra
re
Ite
m
se
t
M
in
in
g
”
.
1
9
th
IEE
E
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
T
o
o
ls
wi
th
Art
if
ici
a
l
In
telli
g
e
n
c
e
.
2
0
0
7
.
P
a
tras
:
3
0
5
-
3
1
2
.
[4
]
S
o
n
g
,
M
.
,
S
a
n
g
u
th
e
v
a
r,
R.
“
A t
ra
n
sa
c
ti
o
n
m
a
p
p
in
g
A
l
g
o
rit
h
m
f
o
r
fre
q
u
e
n
t
it
e
m
-
se
ts
m
in
in
g
”
.
IEE
E
T
ra
n
sa
c
ti
o
n
s o
n
Kn
o
wled
g
e
a
n
d
D
a
ta
En
g
i
n
e
e
rin
g
,
2
0
0
6
;
1
8
(
4
):
4
7
2
–
4
8
1
.
[5
]
A
rn
a
b
Da
s.
“
M
in
in
g
ra
re
it
e
m
se
ts
u
sin
g
b
o
t
h
T
o
p
-
d
o
w
n
a
n
d
Bo
tt
o
m
-
up
a
p
p
ro
a
c
h
”
.
I
n
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
c
o
mp
u
ter
sc
ien
c
e
a
n
d
i
n
f
o
rm
a
ti
o
n
tec
h
n
o
lo
g
ies
.
2
0
1
6
;
7
(3
):
1
6
0
7
-
1
6
1
4
.
[6
]
H.
Yu
n
,
D.
Ha
,
B.
Hw
a
n
g
,
K.
H.
Ry
u
.
“
M
in
i
n
g
a
ss
o
c
iatio
n
ru
les
o
n
sig
n
if
ica
n
t
ra
re
d
a
ta
u
sin
g
re
lativ
e
su
p
p
o
rt
”
.
J
o
u
rn
a
l
o
f
S
y
ste
ms
a
n
d
S
o
f
twa
re
-
El
se
v
ie
r
.
2
0
0
3
;
6
7
:
1
8
1
-
1
9
1
.
[7
]
A
.
L
.
G
re
e
n
ie
G
e
e
v
li
n
,
A
.
M
a
l
a
.
“
Eff
icie
n
t
A
l
g
o
rit
h
m
s
f
o
r
M
in
in
g
Clo
se
d
F
re
q
u
e
n
t
Item
se
t
a
n
d
G
e
n
e
r
a
ti
n
g
Ra
re
A
s
so
c
iatio
n
Ru
les
f
ro
m
Un
c
e
rtai
n
Da
tab
a
se
s
”
.
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
sc
ien
ti
fi
c
re
se
a
rc
h
a
n
d
ma
n
a
g
e
me
n
t
.
2
0
1
3
;
1
(2
):
9
4
-
1
0
8
.
[8
]
S
e
th
i,
S
h
a
rm
a
.
“
Eff
icie
n
t
A
l
g
o
rit
h
m
s
f
o
r
M
in
in
g
Ra
re
Item
se
t
o
v
e
r
T
i
m
e
V
a
rian
t
T
ra
n
sa
c
ti
o
n
a
l
Da
tab
a
se
”
.
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
c
o
mp
u
ter
sc
ien
c
e
a
n
d
i
n
fo
rm
a
t
io
n
tec
h
n
o
lo
g
ies
,
2
0
1
4
;
5
(3
):
3
4
6
5
-
3
4
6
8
.
[9
]
R.
Ud
a
y
Kira
n
,
P
.
Re
d
d
y
.
“
M
in
in
g
ra
re
a
ss
o
c
iatio
n
ru
les
i
n
t
h
e
d
a
tas
e
ts
w
it
h
w
id
e
l
y
v
a
r
y
in
g
it
e
m
s
’
f
re
q
u
e
n
c
ies
”
.
Pro
c
e
e
d
in
g
s
o
f
1
5
th
in
ter
n
a
ti
o
n
a
l
c
o
n
fer
e
n
c
e
o
n
d
a
ta
b
a
se
sy
ste
ms
fo
r A
d
v
a
n
c
e
d
A
p
p
l
ica
ti
o
n
s
.
2
0
1
0
:
1
:
4
9
-
62
[1
0
]
P
ir
i,
De
len
,
L
iu
,
P
a
iv
a
.
“
De
v
e
lo
p
m
e
n
t
o
f
a
n
e
w
m
e
tri
c
to
id
e
n
ti
f
y
ra
re
p
a
tt
e
rn
s
in
a
ss
o
c
iatio
n
a
n
a
ly
sis:
th
e
c
a
se
o
f
a
n
a
ly
sin
g
Dia
b
e
tes
c
o
m
”
.
Exp
e
rt sy
ste
ms
wit
h
a
p
p
li
c
a
ti
o
n
s
,
El
se
v
ier
L
td
,
2
0
1
7
;9
4
:
1
1
2
-
1
2
5
.
[1
1
]
M
u
sta
f
a
M
a
n
,
W
a
n
Ba
k
a
r,
A
b
d
u
ll
a
h
Z,
Ja
li
l
M
,
He
ra
w
a
n
T
.
“
M
in
in
g
A
ss
o
c
iatio
n
ru
les
:
A
c
a
se
stu
d
y
o
n
Be
n
c
h
m
a
r
k
d
e
n
se
d
a
ta
”
.
In
d
o
n
e
si
a
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
r
in
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
.
2
0
1
6
;
3
(3
):
5
4
6
-
5
5
3
.
[1
2
]
K
Ra
jen
d
e
ra
P
ra
sa
d
.
“
Op
ti
m
iz
e
d
Hig
h
-
Util
it
y
it
e
m
se
ts
m
in
in
g
f
o
r
e
ffe
c
ti
v
e
a
ss
o
c
iatio
n
m
in
in
g
p
a
p
e
r
”
.
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
t
e
r E
n
g
i
n
e
e
rin
g
.
2
0
1
7
;
7
(
5
):
2
9
1
1
-
18.
[1
3
]
S
a
d
iq
Hu
s
sa
in
,
Ne
a
m
a
A
b
d
u
laz
izD
a
h
a
n
,
F
a
d
lM
u
tah
e
r
Ba
-
A
lw
i,
Na
jo
u
a
Rib
a
ta.
“
Ed
u
c
a
ti
o
n
a
l
Da
t
a
M
in
in
g
a
n
d
A
n
a
l
y
si
s
o
f
S
tu
d
e
n
ts’
A
c
a
d
e
m
i
c
P
e
rf
o
rm
a
n
c
e
Us
in
g
W
EK
A
”
.
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
Co
mp
u
ter
S
c
ien
c
e
.
2
0
1
8
;
9
(2
):
4
4
7
-
4
5
9
.
[1
4
]
Da
rra
b
,
Erg
e
n
c
.
“
V
e
rt
ica
l
P
a
tt
e
rn
M
in
i
n
g
a
lg
o
rit
h
m
f
o
r
m
u
lt
ip
le
su
p
p
o
rt
t
h
re
sh
o
ld
s
”
.
Pr
o
c
e
e
d
in
g
s
o
f
In
ter
n
a
ti
o
n
a
l
c
o
n
fer
e
n
c
e
o
n
k
n
o
wle
d
g
e
b
a
se
d
a
n
d
i
n
telli
g
e
n
t
in
f
o
rm
a
ti
o
n
a
n
d
e
n
g
in
e
e
rin
g
S
y
ste
ms
.
F
ra
n
c
e
.
2
0
1
7
:
4
1
7
-
4
2
6
.
[1
5
]
El
a
h
e
,
Zh
a
n
g
.
“
M
i
n
i
n
g
f
re
q
u
e
n
t
i
tem
se
ts
a
lo
n
g
w
it
h
ra
re
i
tem
se
ts
b
a
se
d
o
n
c
a
teg
o
rica
l
m
u
lt
ip
le
m
in
im
u
m
su
p
p
o
rt
”
.
J
o
u
rn
a
l
o
f
Co
m
p
u
ter
E
n
g
i
n
e
e
rin
g
,
2
0
1
6
;
1
8
(6
)
:
1
0
9
-
1
1
4
.
[1
6
]
Bh
a
tt
,
P
a
tel,
“
A
No
v
e
l
a
p
p
ro
a
c
h
f
o
r
f
in
d
in
g
ra
re
it
e
m
s
b
a
se
d
o
n
m
u
lt
ip
le
m
in
im
u
m
su
p
p
o
rt
f
ra
m
e
w
o
r
k
”
.
Pro
c
e
e
d
in
g
s
o
f
3
rd
In
ter
n
a
ti
o
n
a
l
c
o
n
fer
e
n
c
e
o
n
re
c
e
n
t
tre
n
d
s
in
c
o
m
p
u
ti
n
g
.
2
0
1
5
;
5
7
:
1
0
8
8
-
1
0
9
5
.
[1
7
]
Ka
n
im
o
z
h
iS
e
lv
i.
“
M
in
in
g
Ra
re
it
e
m
s
e
t
w
it
h
a
u
to
m
a
ted
su
p
p
o
rt
th
re
sh
o
l
d
s
”
.
J
o
u
rn
a
l
o
f
Co
mp
u
ter
sc
ien
c
e
,
2
0
1
1
;
7
(3
):
3
9
4
-
3
9
9
.
[1
8
]
S
rik
a
n
t,
R.
,
A
g
ra
w
a
l,
R.
“
M
in
i
n
g
G
e
n
e
r
a
li
z
e
d
A
ss
o
c
iatio
n
Ru
les
”
.
Fu
tu
re
Ge
n
e
ra
ti
o
n
C
o
mp
u
ter
S
y
s
tem
s
,
1
9
9
7
;
1
3
:
161
–
1
8
0
.
[1
9
]
P
a
d
m
a
v
a
th
y
,
Jo
e
.
“
Ra
re
u
ti
li
t
y
it
e
m
se
t
m
in
in
g
w
it
h
o
u
t
c
a
n
d
id
a
te
g
e
n
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ra
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