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201
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I
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Vo
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7
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No
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6
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Dec
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b
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201
7
:
3
7
0
5
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3
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m
d
esp
ite
t
h
eir
h
ig
h
T
F.I
DF
s
co
r
e.
T
h
er
ef
o
r
e,
R
en
a
n
d
So
h
r
ab
[
2
2
]
p
r
o
p
o
s
ed
a
n
o
v
el
ter
m
w
ei
g
h
ti
n
g
s
ch
e
m
e
f
o
r
au
to
m
at
ic
class
i
f
icat
io
n
ta
s
k
u
s
i
n
g
t
h
e
co
m
b
in
atio
n
o
f
d
o
cu
m
e
n
t
-
b
as
ed
an
d
class
-
b
ased
ap
p
r
o
ac
h
es
ca
lled
T
F.I
DF.I
C
F
an
d
its
v
ar
iatio
n
s
T
F.I
DF.I
C
S
δ
F.
I
n
t
h
is
s
c
h
e
m
e,
t
h
e
i
n
v
er
s
e
class
f
r
eq
u
e
n
c
y
(
I
C
F)
an
d
th
e
in
v
er
s
e
clas
s
s
p
ac
e
d
en
s
it
y
f
r
eq
u
e
n
c
y
(
I
C
S
δ
F)
,
is
in
co
r
p
o
r
ated
.
T
h
e
ex
p
er
im
en
tal
r
esu
l
ts
s
h
o
w
th
at
th
e
p
r
o
p
o
s
ed
class
-
i
n
d
ex
i
n
g
-
b
ased
ter
m
w
eig
h
ti
n
g
ap
p
r
o
ac
h
es
o
u
tp
er
f
o
r
m
ed
T
F.I
DF
an
d
t
h
e
o
th
er
f
iv
e
d
if
f
er
e
n
t te
r
m
w
e
ig
h
ti
n
g
ap
p
r
o
ac
h
es in
a
u
to
m
atic
clas
s
i
f
icat
io
n
tas
k
[
2
2
].
I
n
t
h
is
s
t
u
d
y
,
w
e
h
a
v
e
d
e
v
el
o
p
ed
class
-
b
ased
in
d
e
x
in
g
m
eth
o
d
th
a
t
i
n
co
r
p
o
r
ated
w
it
h
d
o
cu
m
en
t
-
b
ased
in
d
ex
in
g
m
et
h
o
d
f
o
r
Ar
ab
ic
in
f
o
r
m
atio
n
r
etr
iev
a
l.
S
p
ec
if
icall
y
,
w
e
ar
e
co
n
ce
r
n
ed
w
it
h
t
h
e
s
t
u
d
y
o
f
au
to
m
at
ic
r
etr
ie
v
al
o
f
I
s
la
m
i
c
F
iq
h
(
L
a
w
)
b
o
o
k
co
llec
tio
n
.
T
h
is
co
llectio
n
co
n
tai
n
s
m
an
y
b
o
o
k
s
,
ea
c
h
o
f
w
h
ic
h
h
as
te
n
s
to
h
u
n
d
r
ed
s
o
f
p
ag
es.
E
ac
h
p
ag
e
o
f
th
e
b
o
o
k
is
tr
ea
ted
as
a
d
o
cu
m
en
t.
T
h
e
r
etr
iev
al
s
y
s
te
m
w
il
l
r
an
k
t
h
e
b
o
o
k
p
ag
es
b
ased
o
n
th
eir
r
elev
an
ce
to
th
e
u
s
e
r
s
ea
r
ch
ter
m
.
T
h
is
w
o
r
k
w
as
i
m
p
le
m
en
ted
u
s
i
n
g
v
ec
to
r
s
p
ac
e
m
o
d
el
(
VSM)
an
d
co
s
in
e
s
i
m
ilar
it
y
b
ased
o
n
T
F.I
DF.I
C
F
ter
m
w
ei
g
h
t
in
g
.
I
n
th
is
w
o
r
k
,
w
e
al
s
o
p
r
o
p
o
s
e
a
n
o
v
el
book
-
b
ased
in
d
ex
i
n
g
m
e
th
o
d
.
T
h
is
m
et
h
o
d
is
th
e
s
e
m
a
n
tic
v
er
s
io
n
o
f
I
C
F
ca
lled
in
v
er
s
e
b
o
o
k
f
r
eq
u
en
c
y
(
I
B
F)
.
W
e
h
av
e
clas
s
if
ied
th
e
b
o
o
k
p
ag
es
u
s
i
n
g
s
tati
s
tical
clas
s
i
f
ier
to
b
u
ild
th
e
I
C
F
ter
m
w
ei
g
h
ti
n
g
.
T
h
er
ef
o
r
e,
w
e
ca
n
ca
ll
th
e
I
C
F
i
s
u
s
i
n
g
s
tat
is
tical
class
e
s
w
h
ile
t
h
e
I
B
F
is
u
s
in
g
s
e
m
a
n
tic
cla
s
s
e
s
.
T
h
is
s
e
m
a
n
tic
class
is
t
h
e
b
o
o
k
titl
e.
So
m
e
p
ag
es
(
d
o
cu
m
en
ts
)
th
at
s
h
ar
e
th
e
s
a
m
e
b
o
o
k
titl
e
ten
d
to
h
av
e
s
i
m
ilar
co
n
tex
t.
T
h
e
au
th
o
r
h
a
d
m
a
n
u
all
y
co
llected
d
o
cu
m
e
n
ts
t
h
at
d
is
cu
s
s
th
e
s
a
m
e
to
p
ic
o
r
is
s
u
e
in
o
n
e
book
.
N
ea
r
ly
s
i
m
ilar
to
th
e
I
C
F,
I
B
F
co
n
s
id
er
th
e
r
ar
it
y
o
f
t
h
e
ter
m
in
t
h
e
w
h
o
le
b
o
o
k
co
llectio
n
.
T
er
m
s
th
a
t
o
cc
u
r
s
in
m
an
y
b
o
o
k
s
s
h
o
u
ld
n
o
t
b
e
an
i
m
p
o
r
tan
t
ter
m
d
esp
ite
th
eir
h
i
g
h
T
F.I
DF.I
C
F
s
co
r
e.
T
h
e
I
B
F
w
ill
b
e
in
co
r
p
o
r
ated
w
it
h
p
r
ev
i
o
u
s
m
eth
o
d
to
b
e
T
F.I
DF.I
C
F.I
B
F.
T
h
e
ter
m
w
e
ig
h
ti
n
g
m
et
h
o
d
a
ls
o
u
s
ed
f
o
r
f
ea
tu
r
e
s
elec
tio
n
d
u
e
to
h
ig
h
d
i
m
en
s
io
n
alit
y
o
f
t
h
e
f
ea
t
u
r
e
s
p
ac
e.
2.
T
E
RM
WE
I
G
H
T
I
N
G
V
ec
to
r
s
p
ac
e
m
o
d
el
is
a
co
m
m
o
n
m
e
th
o
d
u
s
ed
i
n
I
n
f
o
r
m
atio
n
R
etr
iev
a
l
s
y
s
te
m
.
I
n
v
ec
to
r
s
p
ac
e
m
o
d
el,
ea
c
h
d
o
cu
m
en
ts
i
s
r
ep
r
esen
ted
in
a
m
atr
i
x
t
h
at
co
n
tain
s
it
s
ter
m
s
o
r
w
o
r
d
s
w
ei
g
h
t.
T
h
e
w
eig
h
t
ex
p
r
ess
ed
t
h
e
co
n
tr
ib
u
tio
n
o
f
a
w
o
r
d
o
r
ter
m
to
t
h
e
d
o
cu
m
en
t.
T
h
e
m
ain
f
u
n
ctio
n
o
f
a
ter
m
w
ei
g
h
ti
n
g
s
y
s
te
m
is
th
e
i
m
p
r
o
v
e
m
e
n
t
o
f
r
etr
ie
v
a
l
ef
f
ec
tiv
e
n
es
s
.
P
r
o
p
er
ter
m
weig
h
tin
g
ca
n
g
r
ea
tl
y
i
m
p
r
o
v
e
t
h
e
p
er
f
o
r
m
an
ce
o
f
th
e
v
ec
to
r
s
p
ac
e
m
et
h
o
d
[
2
3
,
2
4
]
.
T
h
er
e
ar
e
s
o
m
e
p
o
p
u
lar
t
er
m
w
ei
g
h
t
in
g
m
et
h
o
d
s
u
c
h
a
s
T
F,
T
F.I
DF
an
d
T
F.I
DF.I
C
F.
2
.
1
.
T
er
m
F
re
qu
e
ncy
(
T
F
)
T
er
m
f
r
eq
u
en
c
y
is
th
e
s
i
m
p
le
s
t
m
et
h
o
d
in
ass
ig
n
i
n
g
w
ei
g
h
t
s
to
ea
c
h
ter
m
.
E
ac
h
ter
m
i
s
a
s
s
u
m
ed
to
h
av
e
a
co
n
tr
ib
u
tio
n
th
a
t
is
p
r
o
p
o
r
tio
n
al
to
th
e
n
u
m
b
er
o
f
i
ts
o
cc
u
r
r
en
ce
s
in
t
h
e
d
o
cu
m
e
n
t.
T
h
e
w
ei
g
h
ts
o
f
ter
m
t in
d
o
cu
m
e
n
t d
u
s
i
n
g
n
o
r
m
alize
d
T
F c
an
b
e
co
u
n
ted
as
f
o
llo
w
s
:
d
t
f
d
t
TF
,
l
o
g
1
)
,
(
(
1
)
w
h
er
e
d
t
f
,
is
t
h
e
n
u
m
b
er
o
f
t
h
e
ter
m
t o
cc
u
r
r
en
ce
i
n
th
e
d
o
cu
m
e
n
t d
.
2
.
2
.
I
nv
er
s
e
Do
cu
m
e
nt
F
re
qu
enc
y
(
I
DF
)
W
h
en
th
e
ter
m
f
r
eq
u
en
c
y
(
T
F)
is
b
ased
o
n
t
h
e
ter
m
o
cc
u
r
r
en
ce
s
i
n
a
d
o
cu
m
en
t,
I
DF
c
o
n
s
id
er
t
h
e
d
is
tr
ib
u
tio
n
o
f
t
h
e
ter
m
in
t
h
e
co
r
p
u
s
.
Un
lik
e
T
F
w
h
ic
h
is
a
lo
ca
l
w
eig
h
ti
n
g
m
et
h
o
d
,
I
DF
is
a
g
lo
b
al
o
n
e.
T
h
e
b
ac
k
g
r
o
u
n
d
o
f
th
is
w
eig
h
ti
n
g
is
a
r
ar
e
ter
m
i
n
th
e
co
r
p
u
s
i
s
v
er
y
v
al
u
ab
le.
T
h
e
v
alu
e
o
f
ea
ch
ter
m
i
s
a
s
s
u
m
ed
to
h
as
th
e
o
p
p
o
s
ite
p
r
o
p
o
r
tio
n
to
th
e
n
u
m
b
er
o
f
d
o
cu
m
e
n
ts
i
n
th
e
co
r
p
u
s
th
at
co
n
tai
n
th
e
t
er
m
.
T
h
e
w
eig
h
t
s
o
f
ter
m
t u
s
in
g
n
o
r
m
alize
d
I
DF
c
an
b
e
co
u
n
ted
as
f
o
llo
w
s
:
t
d
df
N
t
I
D
F
l
o
g
1
)
(
(
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
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C
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I
SS
N:
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c
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p
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tain
s
ter
m
t.
2
.
3
.
I
nv
er
s
e
Cla
s
s
F
re
qu
ency
(
I
C
F
)
I
C
F
is
a
g
lo
b
al
w
ei
g
h
tin
g
m
eth
o
d
lik
e
I
DF.
W
h
e
n
th
e
I
D
F
co
n
s
id
er
th
e
d
is
tr
ib
u
tio
n
o
f
th
e
ter
m
ap
p
ea
r
ea
n
ce
ac
r
o
s
s
th
e
d
o
cu
m
en
ts
i
n
co
r
p
u
s
,
th
e
I
C
F
p
a
y
att
en
tio
n
to
th
e
d
is
tr
ib
u
tio
n
o
f
th
e
ter
m
ap
p
ea
r
ea
n
ce
ac
r
o
s
s
ca
teg
o
r
ies
/
cla
s
s
e
s
.
T
h
e
r
ar
e
ter
m
,
t
h
e
ter
m
t
h
at
o
n
l
y
ap
p
ea
r
s
in
a
ce
r
tain
clas
s
,
h
a
v
e
t
h
e
h
i
g
h
er
v
al
u
e
th
at
th
e
f
r
eq
u
e
n
t
o
n
e
.
T
h
e
v
al
u
e
o
f
ea
c
h
ter
m
i
s
a
s
s
u
m
ed
t
o
h
av
e
t
h
e
o
p
p
o
s
i
te
p
r
o
p
o
r
tio
n
to
t
h
e
n
u
m
b
er
o
f
class
es t
h
at
co
n
tain
t
h
e
ter
m
.
T
h
e
w
eig
h
t
s
o
f
ter
m
t
u
s
in
g
n
o
r
m
alize
d
I
C
F c
a
n
b
e
co
u
n
ted
a
s
f
o
llo
w
s
:
t
c
cf
N
t
I
C
F
l
o
g
1
)
(
(
3
)
w
h
er
e
c
N
is
t
h
e
n
u
m
b
er
o
f
cla
s
s
e
s
an
d
t
cf
is
t
h
e
n
u
m
b
er
o
f
cla
s
s
e
s
th
at
co
n
tai
n
s
ter
m
t.
2
.
4
.
I
nv
er
s
e
B
o
o
k
F
re
qu
e
ncy
(
I
B
F
)
I
B
F
is
a
n
o
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ay
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CO
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m
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n
t
r
e
p
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esen
tatio
n
v
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to
r
s
[
2
5
]
.
Firs
t,
w
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n
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d
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b
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to
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m
w
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h
ti
n
g
m
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h
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d
s
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as T
F,
T
F.I
DF,
T
F.I
DF.I
C
F,
o
r
T
F.
I
DF.I
C
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B
F.
Fig
u
r
e
1
.
C
o
s
in
e
s
i
m
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it
y
r
ep
r
esen
tatio
n
4.
RE
S
E
ARCH
M
E
T
H
O
D
B
r
o
ad
ly
s
p
ea
k
i
n
g
,
th
e
i
n
f
o
r
m
atio
n
r
etr
ie
v
al
s
y
s
te
m
in
t
h
i
s
s
t
u
d
y
co
n
s
is
t
s
o
f
t
h
r
ee
m
ain
s
ta
g
es
,
p
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ce
s
s
in
g
,
f
ea
t
u
r
es
s
elec
t
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n
a
n
d
d
o
cu
m
e
n
t
r
an
k
i
n
g
b
ased
o
n
t
h
e
q
u
er
y
f
r
o
m
u
s
er
.
I
n
t
h
e
f
ir
s
t
s
tag
e,
p
r
ep
r
o
ce
s
s
in
g
,
t
h
er
e
ar
e
s
ev
er
al
s
tep
s
in
cl
u
d
i
n
g
to
k
e
n
iz
atio
n
,
s
to
p
w
o
r
d
s
r
e
m
o
v
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s
t
e
m
m
in
g
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ter
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ca
lc
u
latio
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s
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.
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h
th
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f
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tu
r
e
s
elec
tio
n
s
ta
g
e
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m
e
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est
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ea
t
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s
elec
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f
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m
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.
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h
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s
t
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y
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s
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ased
o
n
th
e
T
F.I
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B
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v
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o
f
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c
h
ter
m
.
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t
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b
es
t
f
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tu
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s
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elec
ted
,
d
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cu
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t
r
an
k
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ta
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e
w
a
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co
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b
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m
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s
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co
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m
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t
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to
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an
d
q
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to
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b
ased
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C
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B
F
ter
m
w
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g
h
ti
n
g
v
al
u
e
.
A
f
ter
th
at,
t
h
e
d
o
cu
m
en
ts
w
ill
b
e
s
o
r
ted
d
escen
d
in
g
l
y
ac
co
r
d
in
g
to
th
eir
co
s
in
e
s
i
m
ilar
it
y
v
al
u
e.
T
h
is
r
an
k
i
n
g
s
h
o
w
s
t
h
e
d
o
cu
m
en
t r
an
k
in
g
r
es
u
lts
ac
co
r
d
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g
to
th
e
le
v
el
o
f
s
i
m
ilar
it
y
to
th
e
u
s
er
q
u
er
y
.
5.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
Data
s
et
t
h
at
h
av
e
b
ee
n
u
s
ed
i
n
t
h
is
e
x
p
er
i
m
e
n
t
is
a
n
A
r
ab
i
c
co
r
p
u
s
w
h
ic
h
i
s
ta
k
en
f
r
o
m
1
3
e
-
b
o
o
k
s
in
Ma
kta
b
a
h
S
ya
mila
h
ap
p
lica
tio
n
.
Si
n
ce
e
v
er
y
p
a
g
es
o
f
t
h
e
b
o
o
k
s
w
a
s
tr
ea
ted
as
a
d
o
cu
m
en
t,
w
e
h
a
v
e
6
9
9
6
d
o
cu
m
en
ts
d
is
tr
ib
u
ted
in
5
ca
t
eg
o
r
ies.
Fro
m
t
h
e
w
h
o
le
d
o
cu
m
en
ts
,
t
h
er
e
ar
e
4
7
.
4
4
7
d
is
tin
c
t te
r
m
s
.
T
h
e
ex
p
er
i
m
en
t
w
a
s
co
n
d
u
c
t
ed
u
s
in
g
7
q
u
er
ies.
E
ac
h
o
f
th
e
q
u
er
ies
h
as
m
o
r
e
th
a
n
o
n
e
r
elev
an
t
d
o
cu
m
en
t.
T
h
e
e
x
p
er
i
m
e
n
t
was
also
co
n
d
u
cted
u
s
in
g
f
ea
t
u
r
e
s
elec
tio
n
th
a
t
v
ar
ies
f
r
o
m
2
5
0
to
1
0
0
0
b
est
f
ea
t
u
r
es.
T
h
e
Gr
o
u
n
d
T
r
u
th
d
ata
th
at
b
ee
n
u
s
ed
i
n
th
i
s
ex
p
er
i
m
en
t
w
er
e
o
b
tain
ed
f
r
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m
a
n
ex
p
er
t.
T
h
e
d
ata
co
n
tain
s
o
m
e
q
u
er
ies
an
d
th
e
co
r
r
esp
o
n
d
in
g
r
elev
a
n
t
d
o
cu
m
en
ts
,
o
r
tech
n
ical
l
y
t
h
e
p
ag
es
o
f
p
ar
ticu
lar
b
o
o
k
s
,
f
o
r
ea
ch
o
f
t
h
e
m
.
I
n
th
i
s
ex
p
er
i
m
en
t,
p
r
ec
is
io
n
,
r
ec
all
an
d
F
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Me
a
s
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m
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th
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ased
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est
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e
atu
r
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y
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o
f
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f
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n
d
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s
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r
e
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f
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%.
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h
e
co
m
m
o
n
ter
m
w
ei
g
h
ti
n
g
m
eth
o
d
,
T
F.I
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en
co
u
n
ter
a
s
ig
n
if
ican
t
lo
s
s
in
p
er
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o
r
m
an
ce
w
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en
u
s
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n
g
f
e
w
er
f
ea
t
u
r
es.
T
h
is
r
es
u
lts
s
h
o
w
ed
t
h
at
th
e
T
F.I
DF
m
e
th
o
d
h
a
s
lo
s
t
a
lo
t
o
f
i
m
p
o
r
ta
n
t
f
e
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es
w
h
e
n
o
n
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y
a
s
m
al
l
n
u
m
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er
o
f
f
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t
u
r
es
u
s
e
d
.
T
h
e
r
esu
lts
a
ls
o
d
ep
icted
t
h
at
t
h
e
T
F.I
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(
w
i
th
o
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t
I
C
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m
eth
o
d
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er
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n
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n
d
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all
v
al
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e
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m
p
ar
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w
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th
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d
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h
is
s
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t
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itio
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a
s
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'
s
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t
u
r
e
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io
n
v
al
u
e
o
f
6
8
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ec
all
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alu
e
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f
6
2
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d
F
-
Me
a
s
u
r
e
v
alu
e
o
f
6
5
%.
I
n
ad
d
itio
n
,
f
r
o
m
T
ab
le
1
,
2
,
an
d
3
ca
n
also
b
e
s
ee
n
t
h
at
th
e
f
ea
t
u
r
es
r
ed
u
ct
io
n
al
s
o
af
f
ec
t
t
h
e
p
er
f
o
r
m
a
n
ce
o
f
ea
c
h
m
et
h
o
d
s
.
T
h
e
f
e
w
er
f
ea
t
u
r
es
u
s
ed
,
th
e
l
o
w
er
p
er
f
o
r
m
a
n
ce
o
b
tain
ed
.
T
F.I
DF
h
a
v
e
a
v
er
y
s
ig
n
i
f
ica
n
t
d
ec
r
ea
s
e
in
p
er
f
o
r
m
an
ce
a
s
th
e
n
u
m
b
er
o
f
f
ea
t
u
r
es
r
ed
u
ce
d
.
T
h
is
is
b
ec
au
s
e
a
lo
t
o
f
im
p
o
r
tan
t
f
ea
t
u
r
es
w
er
e
lo
s
t
d
u
r
in
g
th
e
r
ed
u
ctio
n
.
So
m
e
i
m
p
o
r
ta
n
t
f
e
atu
r
es
h
ad
lo
s
t
b
ec
au
s
e
t
h
e
y
h
av
e
s
m
al
l
T
F.I
DF
v
alu
e
th
a
n
s
o
m
e
o
f
t
h
e
o
th
er
f
ea
t
u
r
es
th
a
t
s
h
o
u
ld
b
e
eli
m
in
ated
.
Un
lik
e
T
F.I
DF,
T
F.I
DF.I
C
F.
I
B
F
s
till
h
as
a
p
r
etty
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o
o
d
p
er
f
o
r
m
an
ce
e
v
e
n
t
h
o
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g
h
u
s
e
a
litt
le
n
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er
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t
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t
h
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m
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th
e
f
ea
t
u
r
es th
a
t h
a
v
e
i
m
p
o
r
tan
t r
o
les.
6.
CO
NCLU
SI
O
N
T
F.I
DF.I
C
F.I
B
F
ter
m
w
ei
g
h
ti
n
g
m
e
th
o
d
ca
n
b
e
ap
p
lied
to
th
e
r
etr
ie
v
al
o
f
A
r
ab
ic
d
o
cu
m
en
ts
t
h
at
h
av
e
a
h
ier
ar
ch
y
o
f
b
o
o
k
s
w
it
h
m
a
n
y
p
ag
es.
T
h
e
ex
p
er
i
m
en
t
r
esu
lts
s
h
o
w
ed
th
a
t
t
h
is
m
et
h
o
d
h
a
s
t
h
e
h
i
g
h
e
s
t
p
r
ec
is
io
n
,
r
ec
all
a
n
d
F
-
Me
as
u
r
e
v
a
lu
e
co
m
p
ar
ed
w
it
h
o
t
h
er
ter
m
w
ei
g
h
ti
n
g
m
e
th
o
d
s
in
cl
u
d
in
g
T
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d
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h
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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I
J
E
C
E
Vo
l.
7
,
No
.
6
,
Dec
em
b
er
201
7
:
3
7
0
5
–
3
7
1
0
3710
v
alu
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f
p
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n
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d
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all
r
ea
ch
es
7
4
%
.
Us
in
g
f
ea
tu
r
e
s
elec
tio
n
,
T
F.I
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C
F.I
B
F
m
eth
o
d
s
t
ill
h
as
a
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ett
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d
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est
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d
th
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-
Me
a
s
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r
e
v
alu
e
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f
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%.
A
s
th
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ter
m
w
ei
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tin
g
m
et
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d
h
ad
s
u
cc
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u
l
ly
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s
ed
in
f
ea
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r
e
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elec
tio
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d
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o
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m
en
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te
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m
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ts
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h
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e
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h
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r
ar
ch
y
o
f
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s
w
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m
a
n
y
p
a
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es
,
i
n
f
u
t
u
r
e
s
t
u
d
ies,
t
h
is
m
et
h
o
d
ca
n
b
e
ap
p
lied
to
th
e
class
i
f
ica
tio
n
o
f
d
o
cu
m
e
n
ts
w
i
th
t
h
e
s
a
m
e
h
ier
ar
ch
y
.
RE
F
E
R
E
NC
E
S
[1
]
Bru
n
n
e
r,
B
.
"
T
h
e
T
i
m
e
A
l
m
a
n
a
c
2
0
0
0
(Bo
st
o
n
,
M
A
:
In
f
o
rm
a
ti
o
n
P
lea
se
LL
C,
1
9
9
9
)
"
.
I
n
Ch
ief,
T
ime
Al
ma
n
a
c
,
(
2
0
0
5
).
[2
]
L
e
w
is,
M
.
P
a
u
l,
G
a
r
y
F
.
S
im
o
n
s,
a
n
d
C
h
a
rles
D.
F
e
n
n
ig
.
Et
h
n
o
lo
g
u
e
:
L
a
n
g
u
a
g
e
s
o
f
th
e
w
o
rld
.
V
o
l
.
1
6
.
Da
ll
a
s,
T
X
:
S
IL
in
tern
a
ti
o
n
a
l,
2
0
0
9
.
[3
]
Lw
in
P
H.
Qu
e
ry
De
p
e
n
d
e
n
t
Ra
n
k
in
g
f
o
r
In
f
o
r
m
a
ti
o
n
Re
tri
e
v
a
l
B
a
se
d
o
n
Qu
e
r
y
Clu
ste
rin
g
.
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
In
fo
rm
a
t
ics
a
n
d
C
o
mm
u
n
ic
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
(
IJ
-
ICT
).
2
0
1
2
No
v
1
7
;
2
(
1
):2
5
-
3
0
.
[4
]
El
ra
o
u
f
,
Esra
a
A
b
d
,
Na
g
w
a
L
o
tfy
Ba
d
r,
a
n
d
M
o
h
a
m
e
d
F
a
h
m
y
T
o
l
b
a
.
"
A
n
Eff
ici
e
n
t
Ra
n
k
in
g
M
o
d
u
l
e
f
o
r
a
n
A
r
a
b
ic
S
e
a
rc
h
En
g
in
e
.
"
IJ
CS
NS
1
0
.
2
(2
0
1
0
):
2
1
8
.
[5
]
M
a
n
n
i
n
g
,
Ch
rist
o
p
h
e
r
D.,
P
ra
b
h
a
k
a
r
Ra
g
h
a
v
a
n
,
a
n
d
Hin
ric
h
S
c
h
ü
t
z
e
.
In
tro
d
u
c
ti
o
n
t
o
i
n
fo
rm
a
ti
o
n
re
triev
a
l
.
Vo
l.
1
.
No
.
1
.
Ca
m
b
rid
g
e
:
Ca
m
b
rid
g
e
u
n
iv
e
rsit
y
p
re
ss
,
2
0
0
8
.
[6
]
En
ik
u
o
m
e
h
in
T
,
S
a
d
ik
u
JS.
T
e
x
t
W
ra
p
p
in
g
A
p
p
ro
a
c
h
t
o
n
a
t
u
ra
l
L
a
n
g
u
a
g
e
In
f
o
r
m
a
ti
o
n
re
tri
e
v
a
l
u
sin
g
sig
n
if
ica
n
t
In
d
ica
to
r
.
IA
ES
In
tern
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
A
rti
f
i
c
ial
In
telli
g
e
n
c
e
.
2
0
1
3
S
e
p
1
;
2
(3
):
1
3
6
.
[7
]
El
Em
a
r
y
,
I.
,
a
n
d
Ja
a
f
a
A
t
w
a
n
.
"
De
sig
n
in
g
a
n
d
B
u
il
d
in
g
a
n
A
u
to
m
a
ti
c
In
f
o
rm
a
ti
o
n
Re
tri
e
v
a
l
S
y
st
e
m
f
o
r
Ha
n
d
li
n
g
th
e
A
ra
b
ic Da
ta."
Ame
ri
c
a
n
J
o
u
r
n
a
l
o
f
A
p
p
li
e
d
S
c
ien
c
e
s
2
.
1
1
(
2
0
0
5
):
1
5
2
0
-
1
5
2
5
.
[8
]
Ha
rra
g
,
F
o
u
z
i,
A
b
o
u
b
e
k
e
u
r
Ha
m
d
i
-
Ch
e
rif
,
a
n
d
Ey
a
s
El
-
Qa
wa
s
m
e
h
.
"
V
e
c
to
r
sp
a
c
e
m
o
d
e
l
f
o
r
A
r
a
b
ic
in
f
o
rm
a
ti
o
n
re
tri
e
v
a
l
—
a
p
p
li
c
a
ti
o
n
to
“
Ha
d
it
h
”
in
d
e
x
in
g
.
"
Ap
p
li
c
a
t
io
n
s
o
f
Dig
it
a
l
In
f
o
rm
a
ti
o
n
a
n
d
W
e
b
T
e
c
h
n
o
lo
g
ies
,
2
0
0
8
.
ICADIW
T
2
0
0
8
.
Fi
rs
t
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
th
e
.
IEE
E,
2
0
0
8
.
[9
]
M
u
sta
f
a
,
S
u
leim
a
n
H.
"
Ch
a
ra
c
ter
c
o
n
ti
g
u
i
ty
in
N
-
g
ra
m
-
b
a
se
d
w
o
rd
m
a
tch
in
g
:
th
e
c
a
se
f
o
r
A
ra
b
ic
tex
t
se
a
rc
h
in
g
.
"
In
fo
rm
a
ti
o
n
p
ro
c
e
ss
in
g
&
ma
n
a
g
e
me
n
t
4
1
.
4
(2
0
0
5
):
8
1
9
-
8
2
7
.
[1
0
]
M
a
y
f
i
e
ld
,
Ja
m
e
s,
e
t
a
l.
"
JH
U/
AP
L
a
t
T
REC
2
0
0
1
:
Ex
p
e
rim
e
n
ts
in
F
il
terin
g
a
n
d
in
A
ra
b
ic,
Vid
e
o
,
a
n
d
W
e
b
Re
tri
e
v
a
l.
"
T
RE
C
.
2
0
0
1
.
[1
1
]
M
u
sta
f
a
,
S
u
leim
a
n
Hu
ss
e
in
.
"
A
r
a
b
ic
strin
g
se
a
rc
h
in
g
i
n
t
h
e
c
o
n
t
e
x
t
o
f
c
h
a
ra
c
ter
c
o
d
e
sta
n
d
a
rd
s
a
n
d
o
rt
h
o
g
ra
p
h
ic
v
a
riatio
n
s."
Co
mp
u
ter
sta
n
d
a
r
d
s
&
in
ter
fa
c
e
s
2
0
.
1
(
1
9
9
8
)
:
3
1
-
5
1
.
[1
2
]
L
a
r
k
e
y
,
L
e
a
h
S
.
,
L
isa
Ba
ll
e
ste
ro
s,
a
n
d
M
a
rg
a
re
t
E.
Co
n
n
e
ll
.
"
L
ig
h
t
ste
m
m
in
g
f
o
r
A
ra
b
ic
in
f
o
rm
a
ti
o
n
re
tri
e
v
a
l.
"
Ara
b
ic co
mp
u
t
a
ti
o
n
a
l
mo
rp
h
o
lo
g
y
.
S
p
rin
g
e
r
Ne
th
e
rlan
d
s,
2
0
0
7
.
2
2
1
-
2
4
3
.
[1
3
]
Ch
e
n
,
A
it
a
o
,
a
n
d
F
re
d
ric C.
G
e
y
.
"
Bu
il
d
in
g
a
n
A
ra
b
ic S
tem
m
e
r
f
o
r
In
f
o
rm
a
ti
o
n
Re
tri
e
v
a
l.
"
T
RE
C
.
Vo
l.
2
0
0
2
.
2
0
0
2
.
[1
4
]
T
a
g
h
v
a
,
Ka
z
e
m
,
Ra
n
ia
El
k
h
o
u
ry
,
a
n
d
Je
ff
re
y
Co
o
m
b
s.
"
A
ra
b
ic
st
e
m
m
in
g
w
it
h
o
u
t
a
ro
o
t
d
icti
o
n
a
r
y
.
"
In
fo
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
:
C
o
d
i
n
g
a
n
d
C
o
mp
u
t
i
n
g
,
2
0
0
5
.
IT
CC
2
0
0
5
.
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
.
V
o
l
.
1
.
IEE
E
,
2
0
0
5
.
[1
5
]
L
a
r
k
e
y
,
L
e
a
h
S
.
,
L
isa
Ba
ll
e
ste
ro
s,
a
n
d
M
a
rg
a
re
t
E.
Co
n
n
e
ll
.
"
Im
p
ro
v
in
g
ste
m
m
in
g
f
o
r
A
ra
b
ic
in
f
o
r
m
a
ti
o
n
re
tri
e
v
a
l:
li
g
h
t
ste
m
m
in
g
a
n
d
c
o
-
o
c
c
u
rre
n
c
e
a
n
a
l
y
sis."
Pro
c
e
e
d
in
g
s
o
f
t
h
e
2
5
th
a
n
n
u
a
l
i
n
ter
n
a
t
io
n
a
l
ACM
S
I
GIR
c
o
n
fer
e
n
c
e
o
n
Res
e
a
rc
h
a
n
d
d
e
v
e
lo
p
me
n
t
in
i
n
fo
rm
a
t
io
n
re
triev
a
l
.
A
CM
,
2
0
0
2
.
[1
6
]
A
b
u
-
S
a
le
m
,
Ha
n
i,
M
a
h
m
o
u
d
A
l
-
O
m
a
ri,
a
n
d
M
a
rth
a
W
.
Ev
e
n
s.
"
S
tem
m
in
g
m
e
th
o
d
o
l
o
g
ies
o
v
e
r
in
d
iv
id
u
a
l
q
u
e
ry
w
o
rd
s
f
o
r
a
n
A
ra
b
ic
in
f
o
r
m
a
ti
o
n
re
tri
e
v
a
l
s
y
st
e
m
.
"
J
o
u
rn
a
l
o
f
th
e
Asso
c
ia
ti
o
n
fo
r
In
f
o
rm
a
ti
o
n
S
c
ien
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
5
0
.
6
(
1
9
9
9
):
5
2
4
.
[1
7
]
Ka
d
ri,
Yo
u
ss
e
f
,
a
n
d
Jia
n
-
Yu
n
Nie
.
"
Eff
e
c
ti
v
e
ste
m
m
in
g
f
o
r
Ara
b
ic
in
f
o
rm
a
ti
o
n
re
tri
e
v
a
l.
"
p
ro
c
e
e
d
in
g
s
o
f
t
h
e
Ch
a
ll
e
n
g
e
o
f
Ara
b
ic f
o
r NL
P/
M
T
Co
n
fer
e
n
c
e
,
L
o
n
d
re
s,
Ro
y
a
u
me
-
Un
i
.
2
0
0
6
.
[1
8
]
S
a
lt
o
n
G
,
Bu
c
k
le
y
C.
Ter
m
-
w
e
i
g
h
ti
n
g
a
p
p
ro
a
c
h
e
s
in
a
u
to
m
a
ti
c
te
x
t
re
tri
e
v
a
l.
In
f
o
r
m
a
ti
o
n
p
ro
c
e
ss
in
g
&
m
a
n
a
g
e
m
e
n
t.
1
9
8
8
Ja
n
1
;
2
4
(
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