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f
E
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Co
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in
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ring
(
I
J
E
CE
)
Vo
l.
7
,
No
.
5
,
Octo
b
e
r
2
0
1
7
,
p
p
.
2
9
1
1
~
2
918
I
SS
N:
2088
-
8708
,
DOI
: 1
0
.
1
1
5
9
1
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e
.
v
7
i
5
.
pp
2
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1
1
-
2
918
2911
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A
s
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le m
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ten
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d
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ter
m
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m
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t
m
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in
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(HU
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)
is
a
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m
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k
n
o
w
n
a
s
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ts.
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a
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m
in
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m
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e
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.
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m
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t
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e
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ra
ti
o
n
,
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it
i
s
f
a
ste
r
th
a
n
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IM
.
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o
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larg
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il
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f
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it
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ll
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s
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m
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tas
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ts.
K
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w
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s
:
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r
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m
in
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FHM
F
r
eq
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s
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C
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1.
I
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RO
D
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O
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Ass
o
ciatio
n
r
u
le
m
in
i
n
g
m
et
h
o
d
s
[
1
]
ar
e
u
s
ed
f
o
r
d
is
co
v
er
in
g
r
u
les
an
d
ite
m
s
t
h
at
ar
e
o
f
f
r
eq
u
en
t
an
d
u
s
er
i
n
ter
ested
ite
m
s
.
E
x
i
s
tin
g
as
s
o
ciatio
n
m
i
n
i
n
g
m
et
h
o
d
s
[
2
-
3
]
u
s
e
th
e
s
u
p
p
o
r
t
-
co
n
f
id
en
ce
f
r
a
m
e
w
o
r
k
[
4
]
in
th
e
d
is
co
v
er
y
o
f
u
s
er
-
i
n
ter
ested
r
u
le
s
.
Ho
w
ev
er
,
t
h
i
s
f
r
a
m
e
w
o
r
k
i
s
n
o
t
s
u
f
f
icie
n
t
f
o
r
m
ea
s
u
r
i
n
g
th
e
u
tili
t
y
o
f
ite
m
s
e
ts
.
I
n
f
i
n
d
in
g
t
h
e
u
til
it
y
o
f
ite
m
s
ets
[
5
]
,
th
e
tr
ad
itio
n
al
s
u
p
p
o
r
t
-
co
n
f
i
d
en
ce
f
r
a
m
e
w
o
r
k
is
en
h
a
n
ce
d
f
o
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m
ea
s
u
r
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g
t
h
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e
m
an
tic
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elatio
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s
a
m
o
n
g
th
e
ite
m
s
w
h
ich
tak
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s
t
h
e
s
e
m
an
t
ic
m
ea
s
u
r
e
o
f
t
h
e
r
u
le
i.
e
th
e
i
m
p
o
r
tan
ce
o
f
t
h
e
ite
m
is
co
n
s
id
er
ed
in
t
h
e
r
u
le.
Fre
q
u
en
t
ite
m
s
et
m
in
in
g
(
FI
M)
[
6
]
is
o
n
e
o
f
th
e
m
o
s
t i
m
p
o
r
tan
t d
ata
m
in
in
g
ta
s
k
an
d
it
i
s
p
o
p
u
lar
in
w
id
e
r
an
g
e
o
f
r
ea
l
lif
e
ap
p
lic
atio
n
s
.
T
h
e
FIM
d
is
co
v
er
s
f
r
e
q
u
en
t
ite
m
s
e
ts
u
s
i
n
g
eit
h
er
Ap
r
io
r
i
o
r
FP
-
g
r
o
w
t
h
[
7
]
f
r
o
m
a
g
iv
e
n
tr
an
s
ac
tio
n
d
atab
ase,
s
o
f
r
eq
u
en
tl
y
ite
m
s
et
s
ar
e
ap
p
ea
r
ed
in
r
esu
lts
o
f
tr
an
s
ac
tio
n
s
.
A
p
r
io
r
i
an
d
FP
-
g
r
o
w
th
m
et
h
o
d
s
g
en
er
ated
th
e
f
r
eq
u
en
t
ite
m
s
et
s
w
it
h
o
u
t
co
n
s
id
er
in
g
th
e
p
r
o
f
i
t
o
f
ite
m
s
et
s
.
I
t
is
e
m
er
g
i
n
g
t
h
at;
w
e
ca
n
al
s
o
co
n
s
id
er
t
h
e
i
m
p
o
r
ta
n
ce
o
f
f
r
eq
u
en
t
ite
m
s
et
s
i
n
ter
m
s
o
f
eit
h
er
a
p
r
o
f
it
o
r
u
tili
t
y
.
Hig
h
Utilit
y
ite
m
s
ets
r
ef
er
s
to
a
s
et
o
f
f
r
eq
u
e
n
t
ite
m
s
w
i
th
h
ig
h
u
til
it
y
.
Hi
g
h
Utili
t
y
ite
m
s
ets
m
i
n
i
n
g
(
HUI
M)
[
8
]
m
et
h
o
d
s
ar
e
p
lay
i
n
g
a
v
ita
l
r
o
le
in
p
r
o
d
u
cin
g
th
e
s
et
o
f
h
i
g
h
u
tili
t
y
f
r
eq
u
e
n
t ite
m
s
et
s
[
9
]
.
Ass
o
ciatio
n
r
u
le
m
i
n
i
n
g
s
y
s
t
e
m
is
o
n
e
o
f
th
e
p
o
p
u
lar
m
et
h
o
d
s
f
o
r
d
is
co
v
er
in
g
o
f
k
n
o
w
led
g
e
d
is
co
v
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y
ab
o
u
t
f
i
n
d
in
g
t
h
e
r
elatio
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s
h
ip
s
a
m
o
n
g
t
h
e
ite
m
s
.
A
i
m
o
f
tr
ad
itio
n
al
as
s
o
ciati
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n
r
u
le
m
in
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(
o
r
A
p
r
io
r
i)
is
to
d
i
s
co
v
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h
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f
r
eq
u
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n
t
i
te
m
s
ets,
w
h
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es
t
h
e
ite
m
s
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f
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s
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t
h
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tr
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d
atab
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O
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li
m
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m
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co
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ce
r
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s
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
5
,
Octo
b
er
201
7
:
2
9
1
1
–
2
9
1
8
2912
ite
m
s
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y
a
n
d
e
x
ter
n
al
u
tili
t
y
[
1
2
-
1
3
]
.
Ke
y
li
m
itatio
n
o
f
FIM
is
t
h
at
i
t
a
s
s
u
m
es
t
h
at
i
m
p
o
r
tan
ce
o
r
p
r
o
f
it
o
f
ea
ch
ite
m
i
s
s
a
m
e
o
r
s
i
m
p
l
y
i
g
n
o
r
ed
th
e
p
r
o
f
it
(
o
r
u
tili
t
y
o
f
ite
m
)
.
Ho
w
ev
er
,
t
h
i
s
ass
u
m
p
tio
n
d
o
es
n
o
t
w
o
r
k
i
n
r
ea
l
l
if
e
ap
p
licatio
n
s
.
T
h
is
p
r
o
b
le
m
i
s
ad
d
r
ess
e
d
in
HUI
M
m
et
h
o
d
.
HUI
M
m
eth
o
d
d
is
co
v
er
s
t
h
e
f
r
eq
u
en
t
ite
m
s
e
ts
w
i
th
h
i
g
h
u
t
ilit
y
.
An
o
t
h
er
ad
v
a
n
ce
d
m
et
h
o
d
,
FHM
i
m
p
r
o
v
e
s
t
h
e
u
tili
t
y
m
i
n
in
g
p
r
o
ce
s
s
w
it
h
r
esp
ec
t
to
s
p
ee
d
p
ar
a
m
eter
.
I
t
is
m
e
m
o
r
y
e
f
f
icien
t,
b
ec
au
s
e
FH
M
u
s
e
s
E
s
t
i
m
a
ted
Util
it
y
C
o
-
Occ
u
r
r
en
c
e
Stru
ct
u
r
e
(
E
UC
S)
[
1
4
]
f
o
r
s
p
ee
d
u
p
th
e
p
r
o
ce
s
s
o
f
h
i
g
h
-
u
til
it
y
ite
m
s
et
m
i
n
i
n
g
.
A
p
r
u
n
i
n
g
s
t
r
ateg
y
[
1
5
]
is
u
s
ed
in
FH
M,
w
h
ic
h
r
ed
u
ce
s
t
h
e
s
e
ar
ch
in
g
s
p
ac
e,
s
o
t
h
at
it
is
s
ix
ti
m
e
s
f
a
s
ter
t
h
an
HUI
M
[
1
6
]
.
L
i
m
it
atio
n
o
f
FHM
is
tak
es
t
h
e
m
o
r
e
co
m
p
u
tatio
n
al
ti
m
e
o
f
E
UC
S
f
o
r
lar
g
e
d
atasets
.
T
h
is
p
ap
er
ex
p
lo
r
es
t
h
e
o
p
ti
m
ized
E
UC
S
an
d
it
i
s
p
r
o
p
o
s
ed
f
o
r
d
is
co
v
e
r
in
g
o
f
e
f
f
icie
n
t
a
n
d
f
aste
s
t
h
i
g
h
-
u
tili
t
y
ite
m
s
et
s
m
i
n
in
g
m
et
h
o
d
.
C
o
n
tr
ib
u
tio
n
s
o
f
th
i
s
p
r
o
p
o
s
ed
w
o
r
k
ar
e
s
u
m
m
ar
ized
as f
o
llo
w
s
:
a.
Dete
r
m
i
n
e
th
e
i
n
ter
n
al
an
d
ex
t
er
n
al
u
ti
lit
y
o
f
ea
ch
a
n
d
ev
er
y
ite
m
s
et
in
t
h
e
tr
an
s
ac
tio
n
a
l d
atab
ase
b.
Min
i
n
g
t
h
e
Hi
g
h
Utilit
y
Fre
q
u
en
t I
te
m
s
ets
c.
Dete
r
m
i
n
i
n
g
t
h
e
h
ig
h
u
tili
t
y
it
e
m
s
et
s
b
ased
r
u
les t
h
at
ar
e
in
t
er
est to
s
tak
e
h
o
ld
er
s
d.
De
m
o
n
s
tr
ate
an
d
s
h
o
w
t
h
e
e
f
f
icie
n
c
y
o
f
p
r
o
p
o
s
ed
u
tili
t
y
-
b
ased
ass
o
ciatio
n
s
y
s
te
m
i
n
t
h
e
ex
p
er
i
m
e
n
tal
s
tu
d
y
u
s
in
g
r
ea
l d
atasets
R
e
m
a
in
i
n
g
s
ec
tio
n
s
o
f
t
h
e
p
ap
er
is
o
r
g
a
n
ized
as
f
o
llo
w
s
:
Sec
tio
n
2
p
r
ese
n
ts
th
e
B
ac
k
g
r
o
u
n
d
s
tu
d
y
o
f
th
e
w
o
r
k
,
Sectio
n
3
d
escr
ib
es
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
o
lo
g
y
,
Sectio
n
4
d
is
c
u
s
s
es
t
h
e
ex
p
er
i
m
e
n
tal
s
tu
d
y
,
a
n
d
Sectio
n
5
p
r
esen
ts
t
h
e
co
n
cl
u
s
io
n
an
d
f
u
t
u
r
e
s
co
p
e.
2.
B
ACK
G
RO
UND
S
T
UD
Y
Sev
er
al
m
eth
o
d
s
ar
e
p
r
o
p
o
s
e
d
f
o
r
HUI
M,
s
o
m
e
o
f
m
et
h
o
d
s
ar
e
alr
ea
d
y
d
is
cu
s
s
ed
i
n
t
h
e
p
ap
er
,
w
h
ic
h
ar
e
P
B
[
1
7
]
,
T
w
o
-
P
h
as
e
[
1
8
]
,
B
A
HUI
[
1
9
]
,
UP
-
g
r
o
w
t
h
[
2
0
]
,
UP
-
g
r
o
w
t
h
+
[
2
1
]
.
T
w
o
-
p
h
ase
m
o
d
el
i
s
to
o
ef
f
icie
n
t,
b
ec
au
s
e
it
s
u
f
f
er
s
f
r
o
m
ex
tr
ac
tin
g
o
f
h
u
g
e
a
m
o
u
n
t
o
f
ca
n
d
id
ates
an
d
r
ep
ea
ted
s
ca
n
s
o
f
d
atab
ase.
HUI
-
Mi
n
er
[
2
1
]
is
p
r
o
p
o
s
ed
t
o
th
e
p
u
r
p
o
s
e
o
f
ex
tr
ac
tin
g
h
i
g
h
-
u
tili
t
y
ite
m
s
e
ts
u
s
i
n
g
a
s
i
n
g
le
p
h
ase.
T
h
er
ef
o
r
e,
it h
ad
b
etter
ap
p
r
o
ac
h
f
o
r
m
i
n
i
n
g
h
i
g
h
-
u
tili
t
y
ite
m
s
ets.
T
h
e
HUI
M
is
o
n
e
o
f
p
o
p
u
la
r
ap
p
r
o
ac
h
f
o
r
d
is
co
v
er
in
g
o
f
h
ig
h
-
u
tili
t
y
i
te
m
s
ets
b
y
T
r
an
s
ac
tio
n
-
W
eig
h
ted
-
Do
w
n
w
ar
d
clo
s
u
r
e
m
o
d
el
[
2
2
]
an
d
it
u
s
es
t
w
o
k
e
y
p
h
a
s
es.
T
w
o
-
p
h
ase,
I
HUP
[
2
3
]
an
d
UP
-
g
r
o
w
t
h
alg
o
r
ith
m
s
ar
e
u
s
ed
t
w
o
p
h
ase
s
.
I
n
a
f
ir
s
t p
h
ase,
t
h
ese
al
g
o
r
ith
m
s
co
m
p
u
te
tr
an
s
ac
tio
n
w
ei
g
h
ted
(
T
W
U)
o
f
g
e
n
er
ated
ca
n
d
id
a
te
h
i
g
h
-
u
ti
lit
y
ite
m
s
e
ts
.
I
n
s
e
co
n
d
p
h
ase,
t
h
ese
al
g
o
r
ith
m
s
f
i
n
d
t
h
e
u
tili
t
y
o
f
o
b
tain
ed
ca
n
d
id
ates
b
y
s
ca
n
n
i
n
g
o
f
d
atab
ase.
H
UI
M
alg
o
r
it
h
m
f
ilter
s
th
e
lo
w
-
u
tili
t
y
ite
m
s
ets
an
d
d
is
co
v
er
s
o
n
l
y
h
i
g
h
-
u
til
it
y
it
e
m
s
et
s
b
y
s
etti
n
g
m
in
i
m
u
m
t
h
r
es
h
o
l
d
u
tili
t
y
v
al
u
e.
FHM
[
2
4
]
c
o
n
s
tr
u
cts
t
h
e
E
UC
S
[
2
5
]
as
p
er
s
eq
u
en
ce
o
f
illu
s
tr
ated
s
tep
s
o
f
Fi
g
u
r
e
1
.
T
h
is
f
i
g
u
r
e
s
h
o
w
s
t
h
e
i
n
p
u
t
d
ata
in
ter
m
s
o
f
tr
an
s
ac
tio
n
d
atab
ase
an
d
u
til
it
y
tab
le.
Utilit
y
tab
le
d
escr
ib
es
th
e
p
r
o
f
it
o
f
ea
ch
ite
m
o
f
tr
an
s
ac
tio
n
al
d
atab
ase.
Fo
r
ex
a
m
p
le,
in
tr
an
s
ac
tio
n
T
1
,
n
u
m
b
er
o
f
ite
m
s
o
f
I
1
is
1
(
it
is
d
ef
i
n
ed
in
Fi
g
u
r
e
1
a
as
I
1
:1
)
,
th
u
s
u
ti
lit
y
b
ec
o
m
e
s
n
u
m
b
er
o
f
ite
m
s
is
m
u
ltip
lied
b
y
p
r
o
f
it
o
f
ite
m
,
as
p
er
th
e
co
m
p
u
tat
io
n
,
u
til
it
y
=1
x
4
=4
.
I
n
Fig
u
r
e
1
c,
T
r
an
s
ac
tio
n
u
t
ilit
y
(
T
U)
is
c
o
m
p
u
ted
b
y
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q
u
atio
n
(
1
)
.
x
T
i
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(
T
i
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f
r
e
q
u
e
n
c
y
(
x
)
p
r
o
f
i
t
(
x
)
(
1
)
T
r
an
s
ac
tio
n
w
ei
g
h
ted
u
tili
t
y
i
s
co
m
p
u
ted
b
y
E
q
u
atio
n
(
2
)
in
Fi
g
u
r
e
1
d
,
E
UC
S
b
y
E
q
u
at
io
n
(
3
)
in
Fig
u
r
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1
e.
i
t
e
m
T
i
T
W
U
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i
t
e
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)
T
U
(
T
i)
(
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{
a
,
b
}
T
i
E
U
C
S
(
a,
b
)
T
U
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T
i
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(
3
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
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8708
Op
timiz
ed
Hig
h
-
Utilit
y
I
temse
ts
Min
in
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fo
r
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A
s
s
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a
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Min
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a
P
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s
a
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2913
T
h
e
alg
o
r
ith
m
o
f
FHM
[
2
4
]
is
as f
o
llo
w
s
A
l
g
o
r
ith
m
1
: FHM
I
n
p
u
t:
D,
a
tr
an
s
ac
tio
n
al
d
atab
ase,
Min
u
til,
a
u
s
er
s
p
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ied
t
h
r
es
h
o
ld
Ou
tp
u
t
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f
h
i
g
h
-
u
t
ilit
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ite
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s
et
s
1.
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ase
‘
D
’
a
n
d
co
m
p
u
t
e
th
e
T
W
U
o
f
s
in
g
le
i
te
m
s
u
s
i
n
g
E
q
u
a
tio
n
(
2
)
2.
Fin
d
h
ig
h
-
u
t
ilit
y
ite
m
s
et
s
u
s
in
g
co
n
d
itio
n
T
W
U(
i)
>
Min
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,
h
er
e
‘
i
’
r
ef
er
s
to
h
i
g
h
-
u
ti
lit
y
i
te
m
3.
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u
ild
th
e
E
UC
S st
r
u
ctu
r
e
u
s
i
n
g
E
q
u
atio
n
(
3
)
4.
Der
iv
e
h
i
g
h
-
u
ti
lit
y
ite
m
s
et
s
u
s
in
g
Sear
ch
p
r
o
ce
d
u
r
e
[
2
4
]
.
(
a)
T
r
an
s
ac
tio
n
al
Data
b
ase
(
b
)
E
x
ter
n
al
Utili
t
y
Va
l
u
e
s
o
f
I
te
m
s
(
c)
T
r
an
s
ac
tio
n
Util
it
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(
d
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T
r
an
s
ac
tio
n
W
eig
h
ted
Utili
t
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(
e)
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S
Fig
u
r
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1
.
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s
tr
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p
r
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s
s
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r
tr
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ata
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ase
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d
u
r
e
in
s
tep
4
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f
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o
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ith
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ts
f
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o
m
s
i
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l
e
ite
m
s
a
n
d
it
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r
ec
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r
s
iv
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y
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e
s
ea
r
ch
s
p
ac
e
o
f
ite
m
s
ets
b
y
ap
p
en
d
in
g
s
in
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le
ite
m
s
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d
it
p
r
u
n
e
s
th
e
s
p
ac
e
b
ased
o
n
f
o
llo
w
i
n
g
p
r
o
p
er
ty
1
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I
n
th
e
i
m
p
le
m
e
n
tat
io
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o
f
p
r
ese
n
t
FHM
s
y
s
te
m
,
b
u
i
ld
in
g
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UC
S
is
a
s
p
ee
d
y
p
r
o
ce
s
s
,
b
ec
au
s
e
it
is
n
o
ted
th
at
f
e
w
ite
m
s
th
at
co
-
o
cc
u
r
i
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th
e
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U
C
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s
o
it
u
s
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e
in
a
m
e
m
o
r
y
.
L
i
m
ited
n
u
m
b
er
o
f
p
air
s
is
co
-
o
cc
u
r
r
ed
f
r
o
m
a
tr
a
n
s
ac
tio
n
al
d
atab
ase.
An
o
th
er
k
e
y
i
m
p
o
r
tan
ce
o
f
F
HM
is
t
h
at
it
b
u
ild
s
t
h
e
E
U
C
S
af
ter
d
eleti
n
g
lo
w
-
u
tili
t
y
ite
m
s
e
ts
i
n
a
s
ea
r
ch
p
r
o
ce
d
u
r
e
o
f
s
tep
4
in
alg
o
r
it
h
m
1
.
P
r
o
p
er
ty
1
[
2
4
]
(
(
s
u
m
o
f
i
u
ti
ls
an
d
r
u
ti
ls
)
.
L
e
t
X
is
a
n
it
e
m
s
et.
L
et
t
h
e
ex
ten
s
io
n
s
o
f
X
b
e
th
e
ite
m
s
ets
t
h
at
ca
n
b
e
o
b
tain
ed
b
y
ap
p
en
d
i
n
g
a
n
ite
m
y
to
X
s
u
c
h
th
a
t
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i
f
o
r
all
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m
i
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X.
I
f
th
e
s
u
m
o
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iu
til
a
n
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r
u
til
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al
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es
i
n
th
e
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tili
t
y
-
li
s
t
o
f
x
is
le
s
s
t
h
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m
i
n
u
t
il,
all
ex
te
n
s
io
n
s
o
f
X
an
d
th
eir
tr
an
s
itiv
e
ex
ten
s
io
n
s
ar
e
lo
w
-
u
tili
t
y
ite
m
s
ets.
Mo
r
e
o
p
tim
ized
E
U
C
S
co
n
s
tr
u
ctio
n
s
tep
s
ar
e
r
eq
u
ir
ed
f
o
r
i
m
p
r
o
v
in
g
o
f
F
HM
a
n
d
p
r
o
p
o
s
ed
OFHM
(
Op
ti
m
ized
E
UC
S b
ased
FH
M)
is
p
r
esen
ted
in
f
o
llo
w
in
g
s
u
b
-
s
ec
tio
n
.
3.
P
RO
P
O
SE
D
WO
RK
T
h
e
k
e
y
n
o
v
e
lt
y
is
to
estab
li
s
h
a
m
ec
h
an
i
s
m
,
w
h
ic
h
is
ca
ll
ed
as
p
r
u
n
in
g
b
ased
E
U
C
S
(
P
E
UC
S).
I
t
eli
m
i
n
ate
s
a
n
e
x
p
en
s
iv
e
j
o
in
o
p
er
atio
n
in
FHM
a
n
d
al
lo
w
s
to
eli
m
i
n
atio
n
o
f
lo
w
-
u
tili
t
y
e
x
te
n
s
io
n
w
it
h
o
u
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
5
,
Octo
b
er
201
7
:
2
9
1
1
–
2
9
1
8
2914
d
ef
in
i
n
g
o
f
u
tili
t
y
lis
t.
Su
p
p
o
s
e,
n
o
tu
p
le
s
ati
s
f
y
i
n
g
th
e
m
i
n
i
m
u
m
u
tili
t
y
a
n
d
th
en
i
g
n
o
r
e
th
e
cu
r
r
en
t
u
tili
t
y
ite
m
an
d
its
s
u
p
er
s
et
s
an
d
th
e
s
e
ite
m
s
ets
n
ee
d
n
o
t
b
e
ex
p
lo
r
ed
.
T
h
is
p
r
o
p
o
s
ed
m
eth
o
d
o
p
ti
m
ize
s
th
e
p
r
o
ce
s
s
o
f
FHM
b
y
i
g
n
o
r
i
n
g
o
r
p
r
u
n
i
n
g
o
f
lo
w
-
u
t
ilit
y
ite
m
s
et
s
.
A
l
g
o
r
ith
m
2
: O
FH
M
I
n
p
u
t
: D
-
tr
an
s
ac
tio
n
al
d
atab
ase,
m
i
n
u
t
il
-
m
i
n
i
m
u
m
u
til
it
y
t
h
r
es
h
o
ld
u
tili
t
y
Ou
tp
u
t
: g
en
er
ati
n
g
h
i
g
h
-
u
ti
lit
y
ite
m
s
ets
a.
Scan
t
h
e
tr
an
s
ac
tio
n
al
d
atab
as
e
w
it
h
u
tili
t
y
v
a
lu
e
s
‘
D’
f
o
r
f
i
n
d
in
g
tr
an
s
ac
tio
n
u
tili
t
y
‘
T
U’
o
f
tr
an
s
ac
t
io
n
s
an
d
T
r
an
s
ac
tio
n
W
eig
h
ted
Uti
lizatio
n
(
T
W
U)
o
f
item
s
b.
Fin
d
h
ig
h
u
tili
t
y
1
-
ite
m
s
e
ts
,
w
h
ic
h
s
ati
f
y
th
e
co
n
d
it
io
n
o
f
T
W
U(
item
)
≥
m
in
u
ti
l
c.
B
u
ild
th
e
E
UC
S st
r
u
ctu
r
e
f
o
r
co
-
ite
m
s
u
s
i
n
g
T
U
d.
P
r
u
n
e
th
e
lo
w
-
u
tili
t
y
i
te
m
s
ets
f
r
o
m
t
h
e
E
U
C
S,
t
h
at
is
,
p
air
(
x
,
y
)
v
a
l
u
e
in
E
UC
S
is
le
s
s
t
h
a
n
m
in
u
til
,
th
e
n
2
-
ite
m
s
et
(
x
,
y
)
i
s
lo
w
-
u
t
ilit
y
ite
m
s
et
an
d
t
h
i
s
2
-
ite
m
s
et
a
n
d
its
s
u
p
er
s
ets
v
al
u
es
ar
e
eli
m
i
n
ated
.
So
,
th
at
n
u
m
b
er
o
f
r
es
u
lti
n
g
h
i
g
h
-
u
tili
t
y
ite
m
s
et
s
is
o
p
ti
m
ized
.
e.
Step
4
is
ap
p
lied
r
ec
u
r
s
iv
el
y
f
o
r
th
e
ex
ten
s
io
n
s
o
f
y
w
h
en
(
x
,
y
)
is
h
i
g
h
-
u
tili
t
y
ite
m
s
et
f
o
r
g
en
er
atin
g
o
f
h
ig
h
-
u
tili
t
y
ite
m
s
e
ts
.
T
h
e
OFHM
p
r
o
ce
d
u
r
e
ta
k
es,
as
i
n
p
u
t
i
s
‘
D
’
(
tr
an
s
ac
tio
n
a
l
d
atab
ase)
an
d
‘
m
i
n
u
til
’
(
t
h
r
esh
o
ld
f
o
r
m
i
n
i
m
u
m
u
tili
t
y
)
.
I
n
Step
1
,
it
s
ca
n
s
t
h
e
en
t
ir
e
tr
an
s
ac
tio
n
al
d
atab
ase
f
o
r
f
in
d
i
n
g
tr
a
n
s
ac
tio
n
al
u
t
ilit
y
(
T
U)
o
f
all
tr
an
s
ac
tio
n
s
an
d
T
W
U
o
f
i
n
d
iv
id
u
al
ite
m
s
.
Step
2
d
eter
m
i
n
es
t
h
e
h
i
g
h
u
t
ilit
y
1
-
i
te
m
s
ets,
w
h
ich
r
e
s
u
l
ts
ar
e
s
atis
f
ied
w
it
h
v
al
u
e
o
f
‘
m
i
n
u
til
’
;
Uti
lit
y
o
f
co
-
ite
m
s
w
it
h
s
ize
o
f
2
i.e
2
-
ite
m
s
e
ts
ar
e
f
o
r
m
ed
in
E
U
C
S
s
tr
u
ct
u
r
e
w
it
h
u
t
ilit
y
i
n
Step
3
.
Step
4
p
er
f
o
r
m
s
t
h
e
o
p
ti
m
izatio
n
s
o
f
E
UC
S;
i.e
lo
w
-
u
ti
lit
y
2
-
ite
m
s
ets
ar
e
eli
m
i
n
ated
o
r
p
r
u
n
ed
in
f
u
r
th
er
s
tep
s
.
T
h
u
s
,
s
ize
o
f
d
ata
o
f
h
i
g
h
-
u
til
it
y
i
te
m
s
ets
is
o
p
ti
m
ized
an
d
au
to
m
at
icall
y
Step
5
p
er
f
o
r
m
s
s
p
ee
d
u
p
th
e
p
r
o
ce
s
s
o
f
d
eter
m
in
in
g
o
f
n
e
x
t
le
v
el
h
i
g
h
-
u
t
i
lit
y
ite
m
s
ets
(
i.e
3
-
ite
m
s
ets,
4
-
i
te
m
s
ets
….
)
.
Hig
h
u
tili
t
y
ite
m
s
et
co
n
s
id
er
s
t
h
e
p
r
o
f
it
a
n
d
q
u
a
n
tit
y
o
f
ite
m
s
ets
o
f
tr
a
n
s
ac
tio
n
al
d
ata
b
ase.
T
h
e
pr
o
b
lem
o
f
h
i
g
h
u
tili
t
y
m
in
i
n
g
is
atte
m
p
ted
in
t
h
e
p
r
o
p
o
s
ed
m
e
th
o
d
.
T
h
is
p
r
o
p
o
s
ed
alg
o
r
i
th
m
ca
n
ef
f
icie
n
tl
y
g
en
er
ate
t
h
e
h
i
g
h
-
u
t
ilit
y
ite
m
s
ets
an
d
it
e
f
f
ec
tiv
e
l
y
ap
p
lied
th
e
p
r
u
n
i
n
g
s
tep
s
f
o
r
r
ed
u
ctio
n
o
f
u
n
p
r
o
m
is
i
n
g
ite
m
s
b
y
s
e
tti
n
g
m
i
n
i
m
u
m
th
r
esh
o
ld
v
al
u
e.
Di
s
co
v
er
i
n
g
t
h
e
p
r
o
m
i
s
in
g
h
i
g
h
-
u
tili
t
y
ite
m
s
e
ts
is
ad
d
r
ess
ed
b
y
p
r
o
p
o
s
ed
OFHM
m
eth
o
d
.
I
t
o
p
tim
izes
t
h
e
s
ize
o
f
p
r
o
m
is
ed
h
ig
h
u
til
it
y
ite
m
s
ets.
T
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
n
ee
d
s
o
n
l
y
a
s
i
n
g
le
p
h
a
s
e
i
n
s
t
ea
d
o
f
t
w
o
-
p
h
ases
.
I
t
co
m
p
u
te
s
th
e
T
U
o
f
tr
an
s
ac
tio
n
s
a
n
d
T
W
U
o
f
in
d
iv
id
u
a
l
ite
m
s
i
n
t
h
e
s
a
m
e
p
h
a
s
e.
I
n
r
ea
l
li
f
e
ap
p
licatio
n
s
,
ac
t
u
al
p
r
o
d
u
cts
h
a
v
e
t
h
e
i
n
f
o
r
m
atio
n
i
n
ter
m
s
o
f
tr
a
n
s
ac
t
io
n
w
it
h
f
r
eq
u
en
c
y
an
d
p
r
o
f
it
(
o
r
u
tili
t
y
)
.
I
n
p
ec
u
liar
s
u
p
er
m
ar
k
et
ap
p
licatio
n
s
,
f
e
w
o
f
p
r
o
d
u
cts
m
a
y
o
cc
u
r
w
it
h
v
er
y
lo
w
f
r
eq
u
e
n
c
y
,
h
o
w
ev
e
r
,
it
m
a
y
w
it
h
h
i
g
h
-
p
r
o
f
it.
I
n
s
u
c
h
p
r
ac
tical
ca
s
es,
t
h
is
p
r
o
p
o
s
ed
m
et
h
o
d
ef
f
ec
tiv
e
l
y
w
o
r
k
s
f
o
r
p
er
f
o
r
m
i
n
g
h
i
g
h
-
u
til
it
y
m
i
n
i
n
g
.
T
r
a
d
itio
n
al
m
e
th
o
d
s
m
a
y
n
o
t
co
n
s
id
er
t
h
e
u
t
ilit
y
o
f
ite
m
s
ets
d
u
r
i
n
g
m
i
n
in
g
p
r
o
ce
s
s
an
d
s
o
m
e
o
th
er
m
eth
o
d
s
ar
e
co
n
s
id
er
e
d
th
e
u
tili
t
y
v
al
u
e,
an
d
th
e
y
r
eq
u
ir
ed
m
u
ltip
le
s
ca
n
s
o
f
d
atab
ase.
I
t i
s
to
o
ex
p
en
s
i
v
e
in
lar
g
e
d
ata
co
m
p
u
tatio
n
o
f
u
tili
t
y
m
in
i
n
g
.
Hig
h
u
til
it
y
ite
m
s
e
t
m
i
n
i
n
g
is
a
m
u
ch
m
o
r
e
d
if
f
ic
u
lt
p
r
o
b
lem
th
a
n
f
r
eq
u
e
n
t
ite
m
s
et
m
in
in
g
.
T
h
er
ef
o
r
e,
alg
o
r
ith
m
s
f
o
r
h
i
g
h
-
u
tili
t
y
ite
m
s
e
t
m
i
n
i
n
g
ar
e
g
en
er
all
y
s
lo
w
er
th
a
n
f
r
eq
u
en
t
ite
m
s
et
m
in
in
g
alg
o
r
ith
m
s
.
T
h
e
p
r
o
p
o
s
ed
m
e
th
o
d
o
lo
g
y
i
s
f
aster
t
h
an
tr
ad
itio
n
al
HUI
M
al
g
o
r
ith
m
f
o
r
d
is
co
v
er
in
g
f
r
eq
u
e
n
t
ite
m
s
ets.
T
h
is
p
r
o
p
o
s
ed
f
r
a
m
e
w
o
r
k
is
u
s
ef
u
l
in
r
ea
l
w
o
r
ld
ap
p
licatio
n
s
s
u
c
h
a
s
e
-
co
m
m
e
r
ce
b
u
s
i
n
es
s
r
etails
ap
p
licatio
n
s
,
w
eb
r
ec
o
m
m
en
d
ed
s
y
s
te
m
s
.
I
n
w
h
ich
,
eit
h
er
p
r
o
f
it
o
r
n
u
m
b
er
o
f
ti
m
es
a
u
s
er
v
is
ited
p
ag
e
is
co
n
s
id
er
ed
as
u
tili
t
y
.
I
t
t
h
en
p
er
f
o
r
m
s
u
tili
t
y
m
in
i
n
g
b
ase
d
o
n
th
is
u
tili
t
y
v
alu
e.
O
n
e
o
f
tr
ad
itio
n
m
et
h
o
d
,
A
p
r
io
r
i
is
u
s
ed
f
o
r
p
r
u
n
in
g
th
e
ca
n
d
id
ate
ite
m
s
ea
r
ch
s
p
ac
e,
b
u
t
th
at
ca
n
n
o
t
ap
p
licab
le
f
o
r
h
ig
h
-
u
til
it
y
ite
m
s
ets,
s
o
,
OFHM
i
s
p
r
o
p
o
s
ed
f
o
r
ad
d
r
ess
in
g
t
h
is
p
r
o
b
le
m
e
f
f
ec
tiv
e
l
y
w
h
e
n
co
m
p
ar
ed
w
i
th
o
t
h
er
u
tili
t
y
m
i
n
in
g
m
et
h
o
d
s
.
I
t
o
p
ti
m
izes
th
e
s
ea
r
c
h
i
n
g
s
p
ac
e,
w
h
ich
en
h
an
c
e
s
t
h
e
p
er
f
o
r
m
a
n
ce
o
f
u
ti
lit
y
m
i
n
i
n
g
tas
k
.
I
t
u
s
e
s
th
e
s
o
m
e
k
in
d
o
f
d
ata
s
tr
u
ctu
r
e,
n
a
m
ed
as
u
til
it
y
-
l
is
t;
t
h
is
i
s
d
ef
i
n
ed
f
o
r
h
i
g
h
u
t
ilit
y
i
te
m
s
e
t.
Su
p
p
o
s
e
th
e
u
tili
t
y
o
f
ite
m
i
s
n
o
t
s
at
is
f
ied
w
it
h
m
in
i
m
u
m
u
tili
t
y
t
h
r
esh
o
ld
v
alu
e,
an
d
th
e
s
u
b
s
eq
u
en
t
u
tili
t
y
lis
t
m
a
y
b
e
u
n
d
e
f
i
n
ed
an
d
th
e
co
r
r
esp
o
n
d
in
g
l
is
t
is
i
g
n
o
r
ed
,
h
en
ce
it
r
etr
iev
es
t
h
e
u
ti
lit
y
-
l
is
t
o
f
h
i
g
h
-
u
tili
t
y
ite
m
s
e
ts
an
d
ig
n
o
r
es
th
e
u
t
ilit
y
-
lis
t
o
f
o
t
h
e
r
ite
m
s
e
ts
.
I
t
i
s
t
h
e
b
est
i
m
p
r
o
v
e
m
e
n
t
s
tep
in
OFHM
th
a
n
o
th
et
u
tili
t
y
m
i
n
i
n
g
m
et
h
o
d
s
.
I
t
u
s
es
t
h
e
s
tr
ateg
y
o
f
p
r
u
n
i
n
g
to
t
h
e
p
u
r
p
o
s
e
o
f
i
g
n
o
r
i
n
g
s
e
v
er
al
j
o
in
o
p
er
atio
n
s
in
o
r
d
er
to
eli
m
i
n
ate
a
lo
w
-
u
tili
t
y
e
x
ten
s
io
n
o
f
s
ev
er
al
u
n
s
atis
f
ied
ite
m
s
u
s
i
n
g
E
UC
S.
T
h
e
E
UC
S
ca
n
b
e
d
en
o
ted
as
a
h
as
h
m
ap
tab
le
a
n
d
t
h
e
r
ele
v
an
t
e
x
a
m
p
le
is
ill
u
s
tr
ated
in
t
h
e
p
r
e
v
io
u
s
s
ec
tio
n
f
o
r
an
al
y
zin
g
t
h
e
p
r
o
b
le
m
o
f
u
tili
t
y
m
i
n
in
g
.
T
h
is
h
as
h
m
ap
is
u
s
ed
in
OF
HM
f
o
r
ac
h
ie
v
i
n
g
o
f
m
e
m
o
r
y
ef
f
icie
n
c
y
,
s
i
n
ce
E
UC
S
is
s
p
ar
s
e
in
n
atu
r
e.
C
o
n
s
tr
u
c
tio
n
o
f
u
ti
li
t
y
-
lis
t
f
r
o
m
OFHM
is
ta
k
e
n
v
er
y
les
s
ti
m
e.
T
h
er
ef
o
r
e,
s
p
ac
e
an
d
ti
m
e
r
eq
u
ir
e
m
e
n
ts
ar
e
o
p
tim
ized
in
OFHM.
E
x
te
n
s
i
v
e
s
t
u
d
y
o
f
ex
p
er
i
m
e
n
tal
r
es
u
lts
o
f
r
ea
l
w
o
r
ld
d
atasets
is
d
is
cu
s
s
ed
in
t
h
e
f
o
llo
w
i
n
g
s
ec
t
io
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2088
-
8708
Op
timiz
ed
Hig
h
-
Utilit
y
I
temse
ts
Min
in
g
fo
r
E
ffective
A
s
s
o
ci
a
tio
n
Min
in
g
P
a
p
er
(
K
.
R
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jen
d
r
a
P
r
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s
a
d
)
2915
4.
E
XP
E
R
I
M
E
NT
A
L
ST
UDY
Su
b
s
ta
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tial
e
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ts
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ar
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as
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u
ti
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t
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ata
s
ets.
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h
e
d
atasets
ar
e
co
llected
f
r
o
m
FIM
I
r
ep
o
s
ito
r
y
[
2
6
]
.
T
ab
le
1
s
h
o
w
s
th
e
ch
ar
ac
ter
s
tics
o
f
t
h
e
d
atasets
.
T
h
e
i
m
p
le
m
e
n
ted
OFHM
m
e
th
o
d
ad
o
p
ts
th
e
p
r
u
n
i
n
g
s
tr
ate
g
y
f
o
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ig
n
o
r
in
g
o
f
u
n
w
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ted
lo
w
-
u
ti
lit
y
i
te
m
s
ets
;
it
ac
t
as
i
m
p
r
o
v
ed
s
tr
ateg
y
,
w
h
cih
r
ed
u
ce
t
h
e
r
escan
o
f
lo
w
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u
tili
t
y
ite
m
s
e
ts
f
o
r
lar
g
e
d
atasets
.
I
t
i
s
s
i
g
n
i
f
ica
b
le
i
m
p
r
o
v
e
m
e
n
t.
P
er
f
o
r
m
a
n
ce
o
f
ex
i
s
iti
n
g
u
t
ilit
y
m
in
i
n
g
m
et
h
o
d
s
,
s
u
c
h
a
s
HUI
M
[
2
3
]
,
FHM
[
2
4
]
,
GHUI
-
Mi
n
er
[
2
7
]
ar
e
co
m
p
ar
ed
w
it
h
OFHM
in
t
h
is
e
x
p
er
i
m
e
n
tal
s
t
u
d
y
.
Op
ti
m
izatio
n
o
f
h
ig
h
-
u
tili
t
y
it
e
m
s
is
p
er
f
o
r
m
ed
i
n
OF
HM
.
E
x
is
ti
m
g
a
n
d
p
r
o
p
o
s
ed
m
eth
o
d
s
ar
e
ex
ec
u
ted
i
n
J
av
a
o
n
E
clip
s
e
n
eo
p
latf
o
r
m
w
it
h
J
DK
1
.
6
.
T
h
ese
ex
p
er
i
m
en
ts
ar
e
co
n
d
u
c
ted
o
n
W
i
n
d
o
w
s
7
p
lat
f
o
r
m
w
it
h
h
ar
d
w
ar
e
o
f
co
r
e
i3
1
.
7
Gh
z
p
r
o
ce
s
s
o
r
w
it
h
3
2
GB
R
AM
.
T
ab
le
1
.
C
h
ar
ac
ter
s
tics
o
f
t
h
e
Data
s
ets
D
a
t
a
se
t
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e
r
o
f
T
r
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n
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t
i
o
n
s
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e
n
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h
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r
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ms
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n
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w
it
h
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llectio
n
o
f
s
e
v
er
al
ite
m
s
,
f
o
r
ex
a
m
p
le,
c
h
ai
n
s
to
r
e
u
tili
t
y
d
ata
s
et
h
av
e
u
s
ed
4
6
8
item
s
f
o
r
tr
an
s
ac
tio
n
s
.
E
ac
h
tr
an
s
ac
tio
n
co
n
s
is
t
s
o
f
co
m
b
in
at
io
n
o
f
ite
m
s
am
o
n
g
4
6
8
ite
m
s
.
Du
r
in
g
u
tili
t
y
i
te
m
s
et
g
en
er
ati
o
n
,
it
is
d
er
i
v
ed
th
at
v
er
y
lar
g
e
n
u
m
b
er
o
f
ite
m
s
ets
ar
e
o
cc
u
r
r
ed
in
a
f
as
h
io
n
o
f
u
tili
t
y
b
ased
1
-
i
te
m
s
ets,
2
-
ite
m
s
et
s
,
….
.
s
o
o
n
.
E
x
is
ti
n
g
HU
I
M,
GUI
Min
er
,
FHM
ar
e
ex
p
er
im
e
n
ted
o
n
lar
g
e
d
atasets
o
f
T
ab
le
1
w
it
h
d
if
f
e
r
en
t
th
r
es
h
o
ld
u
tili
t
y
v
al
u
es
o
r
m
i
n
i
m
u
m
u
tili
t
y
v
al
u
es
f
o
r
g
en
er
atio
n
o
f
h
i
g
h
-
u
tili
t
y
f
r
eq
u
e
n
t
ite
m
s
e
ts
b
ase
d
ass
o
ciatio
n
r
u
les.
I
t
i
s
n
o
t
ed
th
at
FHM
is
ta
k
e
n
les
s
c
o
m
p
u
tatio
n
al
ti
m
e
co
m
p
ar
ed
to
HUI
M,
a
n
d
G
UI
Min
er
m
et
h
o
d
s
.
P
r
o
p
o
s
e
d
OFHM
p
r
u
n
es
th
e
lo
w
-
u
tili
t
y
ite
m
s
et
s
b
y
co
n
s
tr
u
n
ti
n
g
P
E
UC
S,
t
h
er
e
f
o
r
e,
OFHM
o
b
t
ain
s
o
p
ti
m
al
n
u
m
b
er
o
f
u
tili
t
y
ite
m
s
ets
f
o
r
g
en
er
atio
n
o
f
h
i
g
h
u
tili
t
y
b
ases
d
as
s
o
ciatio
n
r
u
l
es.
C
o
m
p
u
tatio
n
al
r
u
m
ti
m
e
is
co
m
p
ar
ed
f
o
r
HUI
M,
GUI
Min
er
,
FHM,
an
d
p
r
o
p
o
s
ed
OFHM
an
d
it
is
d
e
m
o
n
s
tr
ated
in
f
o
llo
w
i
n
g
f
i
g
u
r
es
(
Fig
u
r
e
2
to
Fig
u
r
e
5
)
.
I
t
is
n
o
ted
t
h
at
p
r
o
p
o
s
ed
OFHM
is
f
aster
a
n
d
m
o
r
e
f
it
f
o
r
g
en
er
atio
n
o
f
h
i
g
h
-
u
tili
t
y
b
ased
ass
o
ciatio
n
r
u
les.
Fig
u
r
e
2
.
C
o
m
p
u
tat
io
n
al
r
u
n
ti
m
e
co
m
p
ar
is
o
n
f
o
r
ch
ai
n
s
to
r
e
u
tili
t
y
d
ataset
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
5
,
Octo
b
er
201
7
:
2
9
1
1
–
2
9
1
8
2916
Fig
u
r
e
3
.
C
o
m
p
u
tat
io
n
al
r
u
n
ti
m
e
co
m
p
ar
is
o
n
f
o
r
ch
es
s
u
t
ilit
y
d
ataset
T
h
e
p
er
f
o
r
m
an
ce
o
f
m
et
h
o
d
s
ar
e
co
m
p
ar
ed
b
ased
o
n
th
e
co
m
p
u
tatio
n
r
u
n
ti
m
e.
Fi
g
u
r
e
2
in
d
icate
s
th
at
o
u
r
p
r
o
p
o
s
ed
m
eth
o
d
OF
HM
is
p
er
f
o
m
ed
as
b
etter
an
d
ac
h
iv
e
s
f
a
s
ter
as
s
o
ciatio
n
m
i
n
in
g
r
es
u
lt
s
w
h
e
n
test
ed
w
ith
c
h
ai
n
s
to
r
e
u
t
ilit
y
d
ataset.
Fig
u
r
e
4
.
C
o
m
p
u
ta
t
io
n
al
r
u
n
ti
m
e
co
m
p
ar
is
o
n
f
o
r
f
o
o
d
m
ar
t u
tili
t
y
d
ata
s
et
C
h
o
o
s
i
n
g
o
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ep
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ize
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ets.
Mi
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ataset.
I
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Fi
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r
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4
,
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e
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et
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s
ar
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p
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at
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m
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20000
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an
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it
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h
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i
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F
ig
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e
3
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I
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Fi
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,
co
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m
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o
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x
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g
a
n
d
p
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p
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ed
m
et
h
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d
s
ar
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co
m
p
ar
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w
ith
m
in
i
m
u
m
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es o
f
{5
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4
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}.
T
h
e
GHUI
m
i
n
er
also
m
ak
e
s
th
e
f
a
s
ter
co
m
p
u
tatio
n
o
f
u
ti
li
t
y
m
i
n
i
n
g
r
esu
lt
s
th
a
n
FHM
a
n
d
HUI
M,
h
o
w
ev
er
,
o
u
r
p
r
o
p
o
s
ed
OFHM
is
p
r
u
n
es
th
e
u
n
n
ec
ess
ar
y
lo
w
-
u
til
it
y
ite
m
s
et
s
,
t
h
u
s
,
th
i
s
m
et
h
o
d
i
s
r
ec
o
m
m
e
n
d
ed
as
b
est
f
o
r
h
i
g
h
-
u
tili
t
y
ite
m
s
et
m
in
in
g
.
I
t
is
p
r
o
v
ed
th
at
i
s
u
s
es
a
v
er
y
les
s
m
e
m
o
r
y
t
h
an
o
t
h
er
m
et
h
o
d
s
.
T
h
er
e
it is
also
m
e
m
o
r
y
e
f
f
icien
t.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
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C
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N:
2088
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8708
Op
timiz
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Hig
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2917
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tili
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ca
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t
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etail
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s
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c
h
as
h
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th
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l
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p
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i
tab
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m
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ite
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ce
th
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to
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t
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t
b
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t
les
s
p
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ite
m
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m
s
ets.
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t
is
o
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er
d
t
h
at
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h
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s
h
o
ld
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.
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in
i
m
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m
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if
f
er
en
t
f
o
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ch
d
atase
t,
s
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n
ce
t
h
e
f
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eq
u
en
c
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d
u
til
it
y
o
f
ite
m
s
ets
ar
e
v
ar
ied
f
o
r
d
atase
ts
.
T
h
er
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o
r
e,
in
t
h
e
e
x
p
er
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m
en
tal,
d
if
f
er
e
n
et
t
h
r
es
h
o
ld
v
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s
ar
e
g
iv
e
n
f
o
r
d
if
f
er
en
t
d
atasets
f
o
r
m
ea
s
u
r
i
n
g
t
h
e
co
m
p
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t
at
io
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ti
m
e
o
f
u
ti
lit
y
m
i
n
i
n
g
m
et
h
o
d
s
.
Fro
m
th
e
i
n
v
esti
g
atio
n
o
f
e
x
p
er
i
m
e
n
tal
r
e
s
u
l
ts
o
f
u
tili
t
y
m
in
in
g
m
et
h
o
d
s
,
it
is
n
o
ted
t
h
at
t
h
e
OFHM
d
er
iv
e
s
t
h
e
h
ig
h
-
u
tili
t
y
ite
m
s
e
ts
i
n
a
f
as
ter
w
a
y
th
a
n
o
th
er
m
et
h
o
d
s
.
5.
CO
NCLU
SI
O
N
AND
F
U
T
U
RE
SCO
P
E
T
h
is
p
ap
er
is
m
aj
o
r
l
y
f
o
c
u
s
ed
o
n
ass
o
ciatio
n
m
i
n
i
n
g
m
et
h
o
d
s
f
o
r
ef
f
ec
ti
v
e
g
e
n
er
atio
n
o
f
h
i
g
h
-
u
tili
t
y
ite
m
s
ets.
T
r
ad
itio
n
al
as
s
o
ciati
o
n
m
e
th
o
d
s
d
i
s
co
v
er
f
r
eq
u
en
t
ite
m
s
ets
w
it
h
o
u
t
co
n
s
id
er
i
n
g
eith
er
a
p
r
o
f
i
t
o
r
u
tili
t
y
o
f
ite
m
s
e
ts
.
R
ec
e
n
t
ad
v
an
ce
s
p
r
esen
ted
u
tili
t
y
b
ased
m
i
n
i
n
g
m
eth
o
d
s
a
n
d
th
ese
m
e
th
o
d
s
g
e
n
er
ate
b
o
th
lo
w
a
n
d
h
ig
h
-
u
tili
t
y
ite
m
s
ets.
I
t
is
r
eq
u
ir
ed
t
h
at
p
r
u
n
e
t
h
e
l
o
w
-
u
t
ilit
y
ite
m
s
e
ts
f
o
r
f
a
s
ter
m
i
n
in
g
r
e
s
u
l
ts
.
T
h
e
p
r
o
p
o
s
ed
OFHM
ad
d
r
ess
ed
th
e
p
r
u
n
in
g
p
r
o
b
le
m
f
o
r
eli
m
i
n
a
tio
n
o
f
lo
w
-
u
t
ilit
y
ite
m
s
et
s
; t
h
er
ef
o
r
e,
it g
en
er
ates
h
ig
h
-
u
tili
t
y
ite
m
s
et
s
ef
f
ec
ti
v
e
l
y
in
a
s
h
o
r
ter
ti
m
e
w
h
e
n
co
m
p
ar
ed
to
o
th
er
m
et
h
o
d
s
.
Fu
t
u
r
e
s
co
p
e
o
f
th
e
p
r
o
p
o
s
ed
w
o
r
k
is
th
a
t
to
e
x
te
n
d
th
e
p
r
o
p
o
s
e
w
o
r
k
f
o
r
b
ig
d
at
asets
a
n
d
e
n
h
a
n
ce
th
e
u
tili
t
y
m
i
n
in
g
m
e
th
o
d
s
f
o
r
p
er
f
o
r
m
in
g
o
f
d
is
tr
ib
u
ted
p
r
o
c
e
ssi
ng
f
o
r
b
etter
d
ata
an
al
y
tic
s
ab
o
u
t h
ig
h
-
u
tili
t
y
ite
m
s
et
s
.
RE
F
E
R
E
NC
E
S
[1
]
S
u
sh
il
K
u
m
a
r
V
e
r
m
a
,
R.
S
.
T
h
a
k
u
r,
“
F
u
z
z
y
A
s
so
c
iatio
n
Ru
l
e
M
in
in
g
Ba
se
d
M
o
d
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t
o
P
r
e
d
ict
S
tu
d
e
n
ts’
P
e
rf
o
rm
a
n
c
e
,
”
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
El
e
c
tri
c
a
l
a
n
d
Co
m
p
u
ter E
n
g
in
e
e
rin
g
,
Vo
l.
7
,
N
o
.
4
,
2
0
1
7
[2
]
M
a
d
h
u
G
,
Na
g
a
c
h
a
n
d
rik
a
G
,
“
A
Ne
w
P
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ra
d
ig
m
f
o
r
De
v
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lo
p
m
e
n
t
o
f
Da
ta
I
m
p
u
tatio
n
A
p
p
ro
a
c
h
f
o
r
M
issin
g
V
a
lu
e
Esti
m
a
ti
o
n
,
”
In
tern
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
tri
c
a
l
a
n
d
Co
m
p
u
ter E
n
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,
p
p
:
3
2
2
2
-
3
2
2
8
,
V
o
l.
6
,
No
.
6
,
2
0
1
6
[3
]
G
o
e
th
a
ls,
“
S
u
rv
e
y
o
n
F
re
q
u
e
n
t
P
a
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e
rn
M
i
n
in
g
,
”
m
a
n
u
sc
rip
t,
2
0
0
3
[4
]
P
.
F
o
u
r
n
ier
-
Vig
e
r,
C.
W
u
,
V
.
S
.
T
se
n
g
,
―M
in
in
g
T
o
p
-
K
A
ss
o
c
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n
Ru
les
,
‖
i
n
P
ro
c
.
o
f
In
t’l
C
o
n
f
.
o
n
Ca
n
a
d
ia
n
c
o
n
f
e
re
n
c
e
o
n
A
d
v
a
n
c
e
s in
A
rti
f
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c
ial
In
telli
g
e
n
c
e
,
p
p
.
6
1
–
7
3
,
2
0
1
2
[5
]
H.
Ry
a
n
g
,
U
Yu
n
a
n
d
K.
Ry
u
,
―Disc
o
v
e
rin
g
Hig
h
U
ti
li
ty
Ite
m
se
ts
w
it
h
M
u
lt
ip
le
M
in
im
u
m
S
u
p
p
o
rts,
‖
I
n
telli
g
e
n
t
Da
ta
A
n
a
l
y
sis,
V
o
l.
1
8
(6
),
p
p
.
1
0
2
7
-
1
0
4
7
,
2
0
1
4
[6
]
J.
Ha
n
,
J.
P
e
i
,
a
n
d
Y.
Yi
n
,
“
M
i
n
in
g
F
re
q
u
e
n
t
P
a
tt
e
r
n
s
w
it
h
o
u
t
Ca
n
d
i
d
a
te
G
e
n
e
ra
ti
o
n
,
”
P
ro
c
.
A
CM
S
IG
M
OD
In
t’l
Co
n
f
.
M
a
n
a
g
e
m
e
n
t
o
f
Da
ta,
p
p
.
1
-
1
2
,
M
a
y
2000
[7
]
S
a
v
a
se
r
e
,
E.
Om
i
e
c
in
sk
i,
a
n
d
S
.
B.
Na
v
a
th
e
,
“
A
n
Eff
icie
n
t
A
lg
o
rit
h
m
f
o
r
M
in
in
g
A
ss
o
c
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n
Ru
le
s
in
L
a
rg
e
Da
tab
a
se
s
,
”
in
P
r
o
c
.
2
1
st I
n
t.
C
o
n
f
.
V
e
ry
L
a
r
g
e
Da
tab
a
s
e
s,
1
9
9
5
,
p
p
.
4
3
2
–
4
4
4
.
[8
]
M
.
L
iu
a
n
d
J.
Qu
,
―
M
in
i
n
g
Hig
h
Util
it
y
Ite
m
se
ts
w
it
h
o
u
t
Ca
n
d
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a
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ff
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8
]
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g
li
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t
a
l.
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A
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se
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l
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so
n
g
e
t
a
l.
,
“
B
AH
UI:
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a
st
a
n
d
M
e
m
o
r
y
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ff
icie
n
t
M
in
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o
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s
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ts
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se
d
on
Bit
m
a
p
.
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t.
jo
u
rn
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l
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0
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.
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wa
r
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o
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tree
:
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c
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ra
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.
Krish
n
a
m
u
rth
i
,
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t.
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u
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Yu
n
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.
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a
n
g
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u
,
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rr
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n
In
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tal
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in
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m
w
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ra
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ti
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o
rld
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l
2
0
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5
,
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4
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L
iu
,
W
.
L
iao
,
a
n
d
A
.
Ch
o
u
d
h
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r
y
,
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A
F
a
st
Hig
h
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Item
se
t
s
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in
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g
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lg
o
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m
,
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in
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r
o
c
.
Ut
il
it
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Ba
s
e
d
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ta
M
in
i
n
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rk
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o
p
S
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KD
D,
2
0
0
5
,
p
p
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2
5
3
–
2
6
2
.
[2
5
]
Ch
u
n
-
w
e
i
L
in
e
t
a
l.
,
“
E
ff
icie
n
t
Up
d
a
ti
n
g
of
Disc
o
v
e
re
d
Hi
g
h
-
u
ti
li
ty
Ite
m
se
ts
f
o
r
T
r
a
n
sa
c
ti
o
n
De
letio
n
in
Dy
n
a
m
i
c
Da
tab
a
se
s
,”
A
d
v
a
n
c
e
d
En
g
in
e
e
rin
g
In
f
o
rm
a
ti
c
s,
V
o
l.
2
9
,
p
p
.
1
6
-
2
7
,
2
0
1
5
[2
6
]
h
tt
p
:
//
f
im
i.
u
a
.
a
c
.
b
e
/
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7
]
P
h
il
li
p
p
e
F
o
u
r
n
ier
-
Vig
e
r
e
t
a
l.
,
“
F
HM:
F
a
ste
r
Hig
h
-
u
ti
li
ty
Ite
m
se
t
M
in
in
g
Us
in
g
Esti
m
a
ted
Util
it
y
Co
-
o
c
c
u
rre
n
c
e
P
r
u
n
i
n
g
,
”
L
NA
I
B
I
O
G
RAP
H
Y
O
F
AUTHO
R
Dr.
K.
Ra
jen
d
ra
P
ra
sa
d
G
ra
d
u
a
ted
in
B.
T
e
c
h
(CS
E)
f
ro
m
Ja
wa
h
a
rlal
Ne
h
ru
T
e
c
h
n
o
lo
g
ica
l
Un
iv
e
rsit
y
,
H
y
d
e
ra
b
a
d
in
1
9
9
9
.
He
re
c
e
iv
e
d
M
a
ste
rs
De
g
r
e
e
in
M
.
T
e
c
h
(CS
E)
f
ro
m
V
isv
e
sv
a
ra
y
a
Tec
h
n
o
lo
g
ica
l
Un
i
v
e
rsit
y
,
B
e
lg
a
u
m
,
in
2
0
0
4
.
He
re
c
e
iv
e
d
P
h
.
D
in
Co
m
p
u
ter
S
c
ien
c
e
&
En
g
in
e
e
rin
g
f
ro
m
JN
TUA
,
A
n
a
n
th
a
p
u
r,
i
n
2
0
1
5
.
P
re
se
n
tl
y
,
h
e
is
w
o
rk
in
g
a
s P
ro
f
e
ss
o
r
a
n
d
He
a
d
o
f
CS
E
De
p
t.
,
In
stit
u
te
o
f
A
e
ro
n
a
u
ti
c
a
l
En
g
in
e
e
rin
g
,
Hy
d
e
ra
b
a
d
.
He
h
a
s
m
o
re
th
a
n
3
0
P
u
b
l
ica
ti
o
n
s
in
v
a
rio
u
s
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
ls
a
n
d
Co
n
f
e
re
n
c
e
s.
He
is
a
li
f
e
m
e
m
b
e
r
o
f
CS
I,
a
n
d
m
e
m
b
e
r
o
f
IEE
E.
His res
e
a
rc
h
in
t
e
re
sts a
re
d
a
ta
m
in
in
g
&
d
a
ta w
a
r
e
h
o
u
si
n
g
,
a
n
d
d
a
tab
a
se
s.
Evaluation Warning : The document was created with Spire.PDF for Python.