Internati
o
nal
Journal of Ele
c
trical
and Computer
Engineering
(IJE
CE)
V
o
l.
6, N
o
. 1
,
Febr
u
a
r
y
201
6,
pp
. 36
7
~
37
4
I
S
SN
: 208
8-8
7
0
8
,
D
O
I
:
10.115
91
/ij
ece.v6
i
1.9
019
3
67
Jo
urn
a
l
h
o
me
pa
ge
: h
ttp
://iaesjo
u
r
na
l.com/
o
n
lin
e/ind
e
x.ph
p
/
IJECE
Modelling of E-Governance Fram
ework for Mining Knowledge
fro
m
Massive
Gr
ie
va
nce
Re
dre
ssa
l Da
ta
Sa
ng
eet
h
a
G*, L.
Ma
njuna
t
ha
Ra
o**
* Com
puter S
c
i
e
nce,
Bhar
athi
ar
Univers
i
t
y
,
Coi
m
b
atore,
India
** Departmen
t
o
f
MCA, Dr. Ambedkar Inst
itute of
Technolog
y
,
Bangalor
e
,
India
Article Info
A
B
STRAC
T
Article histo
r
y:
Received Sep 14, 2015
Rev
i
sed
No
v
20
, 20
15
Accepte
d Dec 6, 2015
W
ith the m
a
ssive prolif
erat
ion
of online
appli
c
ations for th
e ci
tiz
ens with
abundant resour
ces, ther
e is a treme
ndous hike in usage of e-governance
platform
s. Right
from
entrepren
e
ur, pla
y
e
r
s, pol
itic
ians, studen
t
s, or an
y
o
n
e
who are highly depending on
web-base
d grievance r
e
dressal networking
site
s,
whic
h gene
ra
te
s loa
d
s of ma
ssive
grievance data th
at
ar
e not on
ly
challenging bu
t also highly
impossible
to und
erstand.
The pr
ime reason
behind this is grievan
ce data
is
m
a
s
s
i
ve in
s
i
ze and the
y
are hig
h
l
y
uns
tructured
.
B
ecaus
e
o
f
this
fact
, th
e pro
pos
ed s
y
s
t
em
att
e
m
p
ts
to
understand th
e p
o
ssibilit
y
of p
e
rf
orm
i
ng knowledge discover
y
pr
ocess from
grievan
ce Data
using conventio
nal data
mining
algorithms. Designed in Jav
a
considering massive number
of online e-go
vernance framework from
civilian’s grievance discussion f
o
rums
, the proposed s
y
stem ev
aluates th
e
effectiven
ess of
performi
ng datamining for Big
d
a
ta.
Keyword:
Dat
a
m
a
nagem
e
nt
Dat
a
m
i
ni
ng
E-G
o
ver
n
m
e
nt
Gri
e
vance
re
dr
essal
K
now
ledg
e d
i
sco
v
e
r
y
Copyright ©
201
6 Institut
e
o
f
Ad
vanced
Engin
eer
ing and S
c
i
e
nce.
All rights re
se
rve
d
.
Co
rresp
ond
i
ng
Autho
r
:
Sangeetha G,
Research Sc
holar,
Com
puter Scie
nce,
Bharathia
r
Uni
v
ersity,
E-Mail: san
g
i
t
h
agov
ind
@
g
m
ail.co
m
1.
INTRODUCTION
The National e
-
Governance
Plan of
In
di
an
Go
ve
rnm
e
nt
seeks t
o
l
a
y
t
h
e f
o
u
n
d
at
i
on a
n
d pr
o
v
i
d
e t
h
e
im
pet
u
s f
o
r l
o
ng
-t
erm
gro
w
t
h
o
f
e-
Governance wit
h
in the co
u
n
t
r
y
.
Thi
s
sect
i
on pr
o
v
i
des
i
n
f
o
rm
ation o
n
creatio
n
o
f
t
h
e rig
h
t
g
o
v
e
rn
an
ce and
institu
tio
n
a
l m
ech
an
ism
s
, sett
in
g
up th
e core in
frastru
c
ture and
po
licies
and
i
m
pl
em
entat
i
on
of
a
n
u
m
b
er
o
f
M
i
ssi
o
n
M
o
de P
r
oject
s
at the
Center,
State and inte
grated
service le
vels.
Sev
e
ral d
i
m
e
n
s
io
n
s
an
d
fact
ors in
fluen
ce the d
e
fin
itio
n
o
f
e-gov
ern
a
n
ce
o
r
electron
i
c go
v
e
rn
an
ce. The word
“electr
o
n
i
c” in th
e ter
m
e-
gover
n
an
ce im
p
lies techn
o
l
o
g
y
dr
iv
en
g
o
v
e
r
n
ance. E-
gov
ern
a
nce is th
e app
licatio
n
of i
n
f
o
rm
at
i
o
n
an
d c
o
m
m
uni
cat
i
on t
ech
no
l
ogy
(
I
C
T
)
f
o
r del
i
v
eri
n
g
g
ove
r
n
m
e
nt
servi
ces, e
x
c
h
an
ge
of
i
n
f
o
rm
at
i
on co
m
m
uni
cat
i
on t
r
ansact
i
o
ns
, i
n
t
e
grat
i
o
n o
f
v
a
ri
o
u
s st
an
d-al
one sy
st
em
s and se
r
v
i
ces be
t
w
een
go
ve
rnm
e
nt
-t
o
-
cust
om
er (G
2
C
),
go
ve
rnm
e
nt
-t
o-
bu
si
ness
(
G
2B
),
g
ove
r
n
m
e
nt
-t
o-
go
ve
r
n
m
e
nt
(G
2G
)
as wel
l
as bac
k
of
fi
ce pr
ocesse
s a
n
d
i
n
t
e
ract
i
o
n
s
wi
t
h
i
n
t
h
e
ent
i
r
e
go
ver
n
m
e
nt
fram
e
wor
k
[1]
.
Th
ro
ug
h e
-
g
o
v
e
rn
an
ce,
g
o
v
e
rn
m
e
n
t
serv
ices will b
e
m
a
d
e
av
ailab
l
e
to citizen
s in
a c
o
nv
en
ien
t
, efficien
t an
d
transp
aren
t
m
a
nner
.
T
h
e t
h
ree
m
a
i
n
t
a
rg
et
gr
o
ups
t
h
at
can
be
di
st
i
n
gui
s
h
e
d
i
n
g
o
v
er
na
nce c
onc
ept
s
a
r
e
go
ve
r
n
m
e
nt
,
ci
t
i
zens and
b
u
s
i
n
esses/
i
n
t
e
re
st
gr
ou
ps
. I
n
e
-
go
ve
rna
n
ce t
h
e
r
e are
n
o
di
st
i
n
ct
bo
u
nda
ri
es.
Gene
ral
l
y
fo
ur
basi
c
m
odel
s
are avai
l
a
bl
e –
g
ove
r
n
m
e
nt
-t
o-
ci
t
i
zen (cust
o
m
e
r), g
o
v
er
n
m
ent
-
t
o
-em
p
l
o
y
ees, g
ove
r
n
m
e
nt
-t
o-
go
ve
rnm
e
nt
an
d g
o
v
er
nm
ent
-
t
o
-
busi
n
ess.
Th
e pri
m
ary
pu
rp
ose
of
o
n
l
i
n
e i
n
f
o
rm
at
i
on cen
t
r
e i
s
t
o
de
vel
o
p a
n
d
maintain a community info
rmation network, which
pr
ovides ope
n
and free access
to online inform
ation
for
th
e citizen
s. The h
a
llm
ark
o
f
th
is co
mm
u
n
ity in
fo
rm
atio
n
network
is th
e ab
ility o
f
th
e g
e
n
e
ral
pu
b
lic to
o
b
t
ai
n
inform
ation that
m
a
y not have been
pre
v
iously, or easily
, accessible to the
m
. The m
a
in task of the grie
vanc
e
handling m
odule is to m
a
intai
n
the
details
gr
ievances recei
ved
from
citizen
s of the
city.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJEC
E V
o
l
.
6, No
. 1, Feb
r
uar
y
20
1
6
:
36
7 – 37
4
36
8
1.
1. B
a
ck
gr
ou
nd
Th
is sectio
n
d
i
scu
sses ab
ou
t th
e ex
isting
lite
ratu
res th
at h
a
s b
een
carried
ou
t till
d
a
te in
th
e area o
f
e-
go
ve
rna
n
ce
fo
un
d
rel
e
va
nt
t
o
pr
op
ose
d
st
u
d
y
.
M
o
ham
m
ed a
n
d
Has
s
o
n
[2]
dem
onst
r
at
ed a
fram
e
wo
r
k
t
h
at
u
s
es
d
a
ta
wareh
o
u
s
e techn
i
q
u
e
s su
ch as m
e
tad
a
ta
commo
n
warehou
se t
o
su
ppo
rt th
e un
iv
ersities’ e-
go
ve
rnm
e
nt
.
R
e
nus
he et
al
. [
3
]
ha
ve
hi
ghl
i
g
ht
ed
t
h
e
im
port
a
nce
o
f
dat
a
m
i
ni
ng
t
echn
o
l
o
gy
t
o
desi
g
n
p
r
o
activ
e serv
i
ces to
redu
ce crim
e
in
cid
e
n
c
es in
th
e p
o
lice statio
n
s
ju
risd
ictio
n
.
Crim
e
in
v
e
stig
ation
h
a
s v
e
ry
si
gni
fi
ca
nt
rol
e
of p
o
l
i
ce sy
st
em
i
n
an
y co
un
try. Mam
p
il
li et
al. [4] studie
d
reveals th
at us
ers and government
agencies
alike
are c
o
m
i
ng to slowly
real
i
ze t
h
at
key
w
o
r
d
-
ba
sed
searc
h
i
s
not
e
n
ou
g
h
a
nd
Sem
a
nt
ic we
b-
base
d applications
nee
d
to be
desi
gne
d
.
Karthika a
nd Ra
ngara
j
[5] used
to
receive
the m
o
res/num
erous of
feed
bac
k
res
u
l
t
s fr
om
user /
s
t
ude
nt
s
rel
a
t
e
d t
o
i
m
prove
the
educational as
well as pe
rformance of educ
ational.
Al
A
j
m
i
et
al
.
[6]
pr
ovi
des i
m
port
a
nce t
o
t
h
e c
o
m
b
i
n
at
i
on
of
We
b Se
r
v
i
ces o
n
t
h
e e
-
Lear
ni
n
g
a
ppl
i
cat
i
on
dom
ain, because Web Se
rvi
ce is the
m
o
s
t
co
m
p
le
x choice for dista
n
ce education duri
n
g these
days.
Mo
h
a
r
a
n
a
et al. [
7
] d
i
scu
ssed d
i
f
f
e
r
e
n
t
issu
es an
d
ch
allen
g
es an
d
su
gg
est
s
a f
r
a
m
e
w
o
r
k
to
b
e
ado
p
t
ed
along
with va
rious technologies nee
d
ed
for succes
sful im
ple
m
entation of E-G
overna
n
ce projec
ts and to overc
o
m
e
the ba
rriers.
Das and Patra
[8] pre
s
ente
d a
design a
p
proach
based
on
th
e serv
ice or
i
e
n
t
ed
p
a
r
a
d
i
gm f
o
r
b
u
ild
i
n
g
E-gov
ern
a
n
ce system
s.
Gu
d
a
v
a
lli et a
l
. [9
] d
i
scu
ssed
th
e ro
l
e
o
f
b
i
o
m
etric au
th
en
ticatio
n in
e-
go
ve
rna
n
ce e
n
vi
r
onm
ent
t
o
p
r
o
v
i
d
e
ser
v
i
ces
e
fficiently a
n
d securely over the inte
rnet.
Desai
[
10]
de
m
onst
r
at
es t
h
e use DM
X
qu
ery
fo
r m
a
ki
ng p
r
edi
c
t
i
o
n fr
om
exi
s
t
i
ng dat
a
m
i
ni
n
g
m
odel
s
. El
i
a
et
al
. [11]
de
ve
l
ope
d LR
fo
r
Nat
u
ral
Lan
g
u
a
ge Pr
ocessi
ng
(NLP
) ap
pl
i
cat
i
ons, c
o
m
pos
ed by
electro
n
i
c
d
i
ctio
n
a
ries m
a
d
e
of term
in
o
l
o
g
i
cal
m
u
ltiw
o
r
d
-
ex
pressi
o
n
s
(M
ach
in
e-Read
able Fo
rm
) and
by lo
cal
gram
m
a
rs (i
n t
h
e f
o
rm
of fi
ni
t
e
-st
a
t
e
aut
o
m
a
t
a
and t
r
a
n
s
d
ucers
– F
S
A/
F
S
T. R
a
o a
n
d
Dey
[
12]
dem
onst
r
at
e
d
ho
w t
e
xt
-m
i
n
ing t
e
c
hni
que
s
can hel
p
i
n
ret
r
i
e
val
o
f
i
n
fo
r
m
at
i
on and
rel
a
t
i
ons
hi
ps
fr
o
m
t
e
xt
ual
dat
a
sou
r
ces
,
t
h
ere
b
y
assi
st
i
ng
p
o
l
i
c
y
m
a
kers i
n
di
sco
v
eri
ng as
soci
a
tion
s
b
e
tween
po
licies an
d
citizen
s’ op
in
i
o
n
s
exp
r
essed
i
n
el
ect
r
oni
c
p
ubl
i
c
fo
r
u
m
s
and
bl
o
g
s et
c.
B
h
a
n
t
i
et
al
.
[1
3]
pr
op
ose
d
E-
g
ove
rna
n
ce
i
m
pl
em
ent
a
t
i
on
f
o
r
hi
g
h
er
ed
ucat
i
o
n
sy
st
em
wi
t
h
t
h
e
use
of
dat
a
wa
reh
o
u
si
n
g
a
n
d
dat
a
m
i
ni
ng
t
echni
que
s.
Dat
a
m
i
ni
ng i
n
E-G
o
ver
n
a
n
ce
pl
ay
s an i
m
por
t
a
nt
rol
e
t
o
ana
l
y
ze dat
a
. Trea
tm
ent
recor
d
s
of m
i
l
l
i
ons
of
pat
i
e
nt
s can be st
o
r
e
d
and c
o
m
put
eri
zed an
d dat
a
m
i
ni
ng t
ech
ni
que
s m
a
y
help i
n
ans
w
e
r
i
n
g seve
ra
l
im
port
a
nt
a
n
d cri
t
i
cal
quest
i
o
ns rel
a
t
e
d
t
o
or
gani
zat
i
o
n [1
4
]
.
W
i
t
h
ou
t
d
a
ta
min
i
n
g
it is
d
i
fficu
lt to realize th
e
fu
ll p
o
t
en
tial
o
f
d
a
ta co
llected
with
in
health
care org
a
ni
z
a
t
i
on as dat
a
un
de
r anal
y
s
i
s
i
s
m
a
ssi
ve, h
i
ghl
y
di
m
e
nsi
onal
,
d
i
st
ri
but
ed
a
n
d
unce
r
t
a
i
n
[1
5]
.
Man
y
o
r
g
a
n
i
zatio
n
s
strug
g
l
e with
th
e
u
tili
zatio
n
of
d
a
ta co
llected
th
roug
h
an
o
r
g
a
n
i
zatio
n
on
line
t
r
ansact
i
o
n
pr
o
cessi
ng
(
O
LTP
) [
16]
sy
st
em
that
i
s
n
o
t
i
n
t
e
grat
e
d
f
o
r
deci
si
on m
a
ki
ng a
nd
pat
t
e
r
n
an
a
l
y
s
i
s
.
Critical case study
of cloud for
datam
i
ning
has
been consi
d
ere
d
in the
work
of ra
dha
et
al.
[17]. Elaachak
et
al. [
1
8
]
h
a
v
e
car
r
i
ed ou
t study f
o
r
desig
i
ng
an
alytics o
n
g
a
mes. For
su
ccessf
u
l
E-g
o
v
e
r
n
an
ce
o
r
g
a
n
i
zatio
n it is
im
port
a
nt
t
o
e
m
power t
h
e
m
a
nagem
e
nt
and
st
aff
wi
t
h
dat
a
wa
re
ho
us
i
ng
base
d
on
cri
t
i
cal
t
h
i
nki
n
g
a
nd
kn
o
w
l
e
d
g
e m
a
nagem
e
nt
t
o
ol
s f
o
r st
rat
e
gi
c
d
eci
si
on m
a
ki
ng
.
Fi
gu
re 1.
Dat
a
M
i
ni
ng
C
y
cl
e
Dat
a
wa
reh
o
u
s
i
ng ca
n
be s
u
p
p
o
r
t
e
d
by
deci
si
on s
u
pp
o
r
t
t
ool
s s
u
c
h
as
d
a
t
a
m
a
rt
, OL
A
P
an
d
dat
a
m
i
ni
ng t
o
ol
s. A dat
a
m
a
rt
i
s
a subset
o
f
d
a
t
a
wareh
o
u
se. It foc
u
ses on
selected
subjec
ts. Online a
n
alytical
p
r
o
cessi
n
g
(OLAP) so
l
u
tio
n p
r
o
v
i
d
e
s a mu
lti-d
i
m
e
n
s
io
nal
v
i
ew of th
e d
a
ta foun
d
i
n
relatio
n
a
l d
a
t
a
b
a
ses.
W
i
t
h
st
ore
d
da
t
a
i
n
t
w
o
di
m
e
nsi
o
nal
f
o
rm
ats OL
AP
m
a
kes i
t
po
ssi
bl
e t
o
anal
y
ze p
o
t
e
nt
i
a
l
l
y
l
a
rge am
ount
o
f
d
a
ta with
v
e
ry fast resp
on
se times an
d
prov
i
d
es th
e
ab
ility
for u
s
ers to
g
o
th
roug
h
t
h
e data an
d
drill d
o
w
n
or
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
Mo
del
l
i
ng
of
E
-
G
o
ver
na
nce
F
r
amew
ork f
o
r
Mi
ni
n
g
K
n
ow
l
e
dge
f
r
o
m
M
a
s
s
i
ve Gri
eva
nce
…
(
S
a
ngeet
ha
G)
36
9
ro
ll up
th
ro
ugh v
a
riou
s d
i
m
e
n
s
io
n
s
as d
e
fin
e
d
b
y
th
e d
a
ta stru
cture. Th
e trad
itio
n
a
l m
a
n
u
a
l d
a
ta an
alysi
s
h
a
s
becom
e
i
n
suf
f
i
c
i
e
nt
and m
e
t
hods
fo
r ef
fi
ci
en
t
com
put
er assi
st
ed anal
y
s
i
s
i
n
di
spe
n
sa
bl
e. A
Dat
a
W
a
re
h
o
u
s
e i
s
a se
m
a
ntically
consistent data store that serves as a
phy
si
cal
im
pl
em
ent
a
t
i
on
of a deci
si
o
n
su
pp
o
r
t
dat
a
m
odel
and
st
o
r
es t
h
e i
n
f
o
rm
at
i
on o
n
whi
c
h a
n
e
n
t
e
r
p
ri
se
nee
d
s t
o
m
a
ke st
rat
e
gi
c
deci
si
o
n
s.
1.
2. T
h
e Pr
obl
em
The
g
ove
r
n
m
e
nt
o
f
I
ndi
a,
l
i
k
e al
l
o
v
er
t
h
e
wo
rl
d
,
has
be
g
a
n i
n
vest
i
n
g l
a
rge
am
ount
s i
n
I
n
f
o
rm
at
i
on
and C
o
m
m
uni
cat
i
on Tec
h
n
o
l
ogy
(IC
T
)
.T
he
ob
ject
be
hi
n
d
t
h
ese i
n
vest
m
e
nt
i
s
t
o
im
pro
v
e t
h
e ef
fi
ci
en
cy
of
go
ve
rnm
e
nt
f
u
nct
i
o
n
by
, es
p
eci
al
l
y
enabling citizen ce
ntric services. T
h
ere a
r
e s
o
m
e
technical iss
u
e
whic
h
need t
o
be
di
s
c
usse
d apa
r
t
fr
om
above m
e
nt
i
oned i
s
s
u
e. T
h
e A
b
ove m
e
nt
i
oned i
s
s
u
e ca
n be
res
o
l
v
e
d
by
t
h
e
go
ve
rnm
e
nt
bu
t
as far a
s
t
ech
ni
cal
i
ssues a
r
e concerne
d they need m
o
re
fo
cu
s t
o
reso
lve th
e issu
e. Some of
technical iss
u
e
s
related t
o
e
-
gove
rnance
are:
Tech
ni
cal
I
n
f
r
a
s
t
r
uct
u
re s
u
pp
o
r
t
by
t
h
e
go
ver
n
m
e
nt
C
o
l
l
ect
i
on
of
L
a
rge
am
ount
of
dat
a
Analysis
of the
data So t
h
at ac
curate
Decision ca
n
be m
a
de
Onl
i
n
e
S
u
p
p
o
rt
t
o
al
l
de
pa
rt
m
e
nt
o
f
G
ove
rn
m
e
nt
or
ga
ni
zat
i
o
n
Retriev
a
l of mean
ing
f
u
l
Data
Prese
n
t
a
t
i
on
o
f
m
eani
ngf
ul
da
t
a
so
fast
deci
si
on
can
be
m
a
de
E-
gov
ern
a
n
ce,
m
ean
in
g
th
e
electr
o
n
i
c-
gover
n
an
ce,
h
a
s ev
o
l
v
e
d
as an
in
fo
r
m
atio
n
age
m
o
d
e
l o
f
g
o
v
e
rn
an
ce t
h
at seek
s to
realize p
r
o
cess
an
d stru
cture
fo
r h
a
rsh
e
n
i
n
g
th
e
p
o
t
en
tialiti
es of i
n
fo
rm
at
io
n
&
com
m
uni
cat
i
on t
ech
nol
ogi
e
s
at
vari
o
u
s
l
e
vel
of
go
ve
rnm
e
nt
and
p
ubl
i
c
sect
o
r
.
E-g
o
v
er
na
nce
i
s
t
h
e
co
mmit
m
en
t to
u
tilize app
r
opriate techn
o
l
o
g
ies to
enh
a
n
c
e
g
o
v
e
rn
m
e
n
t
al relatio
n
s
h
i
p
s
i
n
ord
e
r t
o
en
cou
r
ag
e
th
e fair
& efficien
t d
e
liv
ery
o
f
serv
ices. The ICT m
o
d
e
l uses th
e n
e
w tech
no
log
i
es to
main
tain
th
e data in
go
ve
rnm
e
nt
or
gani
zat
i
o
n.
So
m
e
of t
h
ese a
r
e di
sc
usse
d i
n
t
h
i
s
pa
per
w
h
i
c
h i
s
very
p
o
p
u
l
a
r t
e
c
h
n
o
l
o
gi
es n
o
w
-
a-day
s
.
Inc
r
ea
si
ngl
y
,
g
o
v
er
n
m
ent
orga
ni
za
t
i
on, are a
n
al
y
z
i
ng c
u
r
r
ent
a
nd
hi
st
o
r
i
c
dat
a
t
o
i
d
ent
i
f
y
usef
ul
p
a
ttern
s
fro
m
t
h
e larg
e
d
a
tabase so
th
at th
ey can
sup
p
o
r
t
th
eir bu
sin
e
ss strateg
y
Th
eir
main
e
m
p
h
a
sis is on
com
p
l
e
x, i
n
t
e
r
act
i
v
e, expl
ora
t
ory
anal
y
s
i
s
of very
l
a
rge
da
t
a
set
creat
ed by
t
h
e i
n
t
e
grat
i
o
n of
dat
a
fr
om
acros
s
all th
e p
a
rt of th
e
o
r
g
a
n
i
zati
o
n and
t
h
at data is fair
ly static Th
ree com
p
le
men
t
ary trend
s
are th
ei
r Data
ware
h
ouse
,
OL
AP,
Data M
i
ning
.
1.
3. T
h
e Pr
op
osed
Sol
u
ti
o
n
The
prim
e aim of the
propose
d syst
em
is to create a
fra
m
ework
fo
r
gri
e
vance
re
dr
essal
b
o
ar
d i
n
exi
s
t
i
ng e
-
g
o
v
e
r
na
nce f
r
am
ewor
k w
h
e
r
e t
h
e
eval
uat
i
o
n o
f
c
o
n
v
e
n
t
i
onal
da
t
a
m
i
ni
ng al
go
ri
t
h
m
i
s
carri
ed
out
to
check t
h
e ef
fi
c
i
ency
of k
n
o
w
l
e
dge
di
sco
v
ery
of l
a
rge
dat
a
o
f
gri
e
vance
s
am
ong t
h
e ci
vi
l
i
ans i
n
e-g
o
v
er
nanc
e
fram
e
wor
k
.
A
n
e-
go
ver
n
a
n
c
e
fram
e
wor
k
i
s
desi
g
n
ed t
h
a
t
perf
orm
s
sem
a
nt
i
c
eval
uat
i
on f
o
r
vi
sual
i
z
i
ng t
h
e
b
o
ttlen
e
ck
o
f
cu
rren
t app
r
o
a
ch
an
d n
e
ed
o
f
fu
ture
d
e
v
e
l
o
pmen
t o
f
larg
e stream
s o
f
grievan
ce
d
a
ta b
y
an
alytic
approach
on the local m
ach
i
n
e. A
n
arc
h
i
t
ect
ure
has
bee
n
d
e
vel
o
ped
(as s
h
o
w
n i
n
Fi
gu
r
e
2)
, w
h
er
e a p
o
ssi
bl
e
scenari
o
o
f
g
r
i
e
vance
re
dress
a
l
dat
a
gene
rat
i
on i
s
s
h
own.
The arc
h
itecture also
re
prese
n
ts the educati
onal
dat
a
gene
rat
e
d
fr
om
t
h
e ci
vi
l
i
an’s c
o
m
m
uni
ty
usi
ng va
ri
o
u
s
onl
i
n
e g
r
i
e
va
nce fo
r
u
m
s
an
d t
h
ere
b
y
gi
vi
n
g
bi
rt
h
t
o
l
a
rge
r
si
ze of
fi
l
e
s. The
g
r
i
e
va
nce dat
a
di
scussi
o
n
f
o
r
u
m
s
are freq
u
e
nt
l
y
used
by
vari
ous
p
o
l
i
c
y
m
a
kers
fr
om
vari
o
u
s
d
o
m
a
i
n
and
ex
p
e
rt
i
s
e an
d
he
nc
e di
f
f
ere
n
t
t
ypes of
unstructured data
are
ca
ptured. T
h
e
fee
dbac
k
syste
m
in
co
rp
orates th
e
b
a
sic
so
urce
o
f
d
a
ta
g
e
n
e
ration
as t
h
e civ
ilian
s
li
ke to
sh
are
v
a
riou
s
p
e
rcep
tion
s
ab
ou
t
di
ffe
re
nt
soci
al
i
ssues usi
n
g v
a
ri
o
u
s t
y
pes of
dat
a
. The dat
a
m
a
y be i
n
t
e
xt
form
at
or i
n
im
age form
at
or i
n
ot
he
r m
u
l
t
i
m
e
di
a f
o
rm
at
s. Howe
ve
r, f
o
r ea
si
ness i
n
c
o
m
put
at
i
on,
we c
o
nsi
d
e
r
t
h
at
t
h
e
dat
a
i
s
i
n
t
e
xt
fo
rm
at
onl
y
.
O
b
vi
o
u
sl
y
,
such
dat
a
ar
e hi
g
h
l
y
unst
r
u
c
t
u
re
d i
n
si
ze whi
c
h i
s
alm
o
st
im
possi
bl
e t
o
perf
o
r
m
any
sort
s o
f
anal
y
s
i
s
o
n
i
t
.
M
o
reo
v
er
,
per
f
o
r
m
i
ng co
nve
nt
i
o
nal
dat
a
m
i
ni
ng t
ech
n
i
ques
o
v
er l
a
rge
dat
a
i
s
h
i
ghl
y
co
m
p
u
t
atio
n
a
l
ch
allen
g
i
ng
task
.
Hen
c
e, in
t
h
is p
a
p
e
r,
we
try to
bu
ild
a
co
m
p
u
t
atio
n
a
l
co
st efficien
t
m
o
d
e
l
usi
n
g
n
ovel
da
t
a
m
i
ni
ng al
g
o
r
i
t
h
m
.
D
o
cum
e
nt
cl
ust
e
ri
n
g
i
s
an
ena
b
l
i
n
g
t
echni
q
u
e
f
o
r
m
a
ny
ot
he
r m
achi
n
e
learn
i
ng
ap
p
l
i
catio
n
s
, su
ch
as in
fo
rm
atio
n
classifica
tio
n
,
filterin
g
,
ro
u
t
in
g
,
t
o
p
i
c track
i
ng
, an
d
n
e
w ev
en
t
d
e
tectio
n. To
day, d
y
n
a
m
i
c d
a
ta stream
clu
s
tering
p
o
ses sign
ifican
t
ch
allen
g
es to trad
ition
a
l meth
od
s.
Ty
pi
cal
l
y
, cl
us
t
e
ri
ng
al
g
o
ri
t
h
m
s
use t
h
e Vec
t
or
Space
M
o
d
e
l
(V
SM
) t
o
e
n
code
d
o
c
u
m
e
nt
s
2.
RESEARCH METHO
D
OL
OGY
The VSM
rel
a
t
e
s t
e
r
m
s t
o
doc
um
ent
s
, and si
nce di
f
f
ere
n
t
t
e
rm
s have di
ffe
r
e
nt
im
port
a
nce
i
n
a gi
ven
doc
um
ent, a term
weight is associated wi
th every
t
e
rm
. These t
e
rm
wei
g
ht
s are o
f
t
e
n deri
ved
fr
om
t
h
e
fre
que
ncy
o
f
a t
e
rm
wi
t
h
i
n
a doc
um
ent
or set
of
do
cu
m
e
nt
s. M
u
ch
t
e
rm
wei
ght
i
ng sch
e
m
e
s have bee
n
pr
o
pose
d
.
M
o
s
t
of
t
h
ese
exi
s
t
i
ng m
e
t
h
o
d
s
w
o
r
k
u
nde
r t
h
e a
ssum
p
t
i
on t
h
at
t
h
e
wh
ol
e
dat
a
set
i
s
a
v
ai
l
a
b
l
e and
static. Fo
r
i
n
stan
ce, in or
d
e
r
to
u
s
e t
h
e popu
lar
Ter
m
Fr
eq
u
e
n
c
y –
In
v
e
r
s
e Do
cu
m
e
n
t
Fr
eq
u
e
n
c
y (
T
F-
ID
F)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJEC
E V
o
l
.
6, No
. 1, Feb
r
uar
y
20
1
6
:
36
7 – 37
4
37
0
app
r
oach
an
d i
t
s vari
a
n
t
s
,
on
e
nee
d
s t
o
k
n
o
w
t
h
e
num
ber
of
doc
um
ents in
whic
h a te
rm
occurred at least once
(d
oc
um
ent
fre
que
ncy
)
. T
h
i
s
req
u
i
r
es
a
pri
o
ri
k
n
o
wl
e
dge
of
t
h
e
dat
a
,
an
d t
h
at
t
h
e
dat
a
set
d
o
es
n
o
t
c
h
an
ge
d
u
ring
th
e calcu
latio
n
o
f
term weigh
t
s. Th
e
n
eed
fo
r
kn
owled
g
e
o
f
t
h
e entire d
a
ta set sig
n
i
fican
tly li
mits th
e
use
of these
sc
hem
e
s in applications
where continuous data
stream
s
m
u
st
be a
n
alyzed i
n
real
-tim
e. For eac
h
n
e
w do
cu
m
e
n
t
, th
is limitat
i
o
n
lead
s to th
e
upd
ate of t
h
e
doc
um
ent
freq
u
e
n
cy
of
m
a
ny
t
e
rm
s and t
h
ere
f
o
r
e, al
l
p
r
ev
iou
s
ly g
e
nerated
term
we
ig
h
t
s n
e
ed
s recalib
ratio
n.
The
schem
a
tic arc
h
itecture of
th
e p
r
opo
sed
stu
dy is as
sho
w
n as
bel
o
w
Fi
gu
re
2.
Sc
he
m
a
t
i
c
Archi
t
ect
ure
of
St
u
d
y
Fo
r
N do
cu
m
e
n
t
s in
a d
a
ta stream
, th
e co
mp
u
t
ation
a
l co
mp
lex
ity is O(N
2
), assu
m
i
n
g
that th
e ter
m
space M
pe
r
docum
e
nt is m
u
ch less
tha
n
t
h
e num
b
er
of
docum
ents. Othe
rwise, t
h
e c
o
m
putational c
o
m
p
lexity
is O
(N
2
M
l
o
g
M
), whe
r
e O(
M
l
ogM
) com
put
at
i
ons
ar
e ne
eded
to update
a
docum
e
nt.
The
p
r
o
p
o
sed
sy
st
em
consi
d
ers t
h
at
di
ffe
re
nt
onl
i
n
e
u
s
er
’
s
gi
ves
fee
d
s
r
e
l
a
t
e
d t
o
soci
a
l
gri
e
vanc
e
issu
es
fro
m
mu
ltip
le on
lin
e
civ
ilian
n
e
t
w
ork
i
n
g
fo
ru
m
s
. In ord
e
r t
o
co
nsid
er th
e ch
allen
g
e
s, t
h
e stu
d
y
co
nsid
ers all on
lin
e civ
ilian
network
i
n
g
forum
s
wh
ich
ar
e
o
n
t
h
e n
e
t
w
ork. As civ
ilian’s
feedb
a
ck
p
e
rtain
i
n
g
to
g
r
iev
a
n
ce will d
i
ffer
h
i
gh
ly fro
m
o
n
e
to
an
o
t
h
e
r, so
p
r
op
o
s
ed
system
i
s
co
nsid
ered
to h
a
v
e
h
i
gh
n
u
m
b
er of
m
i
ssi
ng dat
a
,
noi
sy
dat
a
, or u
n
am
bi
gu
o
u
s dat
a
, w
h
i
c
h are p
r
e-
pr
o
cessed by
cl
eani
n
g o
p
erat
i
on i
n
con
v
e
n
t
i
onal
d
a
t
a
m
i
ni
ng t
ech
ni
q
u
e. T
h
e
uns
t
ructured
data being collected
i
s
sub
j
ect
e
d
t
o
ope
n s
o
u
r
ce
APIs
f
o
r
ex
tr
acting
t
h
e
k
now
ledg
e
f
r
o
m
u
n
s
tru
c
tur
e
d
d
a
ta.
Th
e an
ticip
ated
issues in
th
e pr
oposed
system
ar
e h
i
gh
ly
l
i
k
el
y
t
o
occu
r
as t
h
e dat
a
i
s
m
a
ssi
ve and
hi
ghl
y
u
n
st
ructured. M
o
re
ove
r,
the study eases
the com
putation
by
not
co
nsi
d
e
r
i
n
g ot
he
r fi
l
e
form
at
and onl
y
consi
d
e
r
ed t
e
xt
fi
l
e
wi
t
h
unst
r
uct
u
re
d d
a
t
a
. The fram
e
wo
r
k
capt
u
res t
h
e
d
a
t
a
fr
om
one r
o
w a
n
d c
h
eck
fo
r n
o
i
s
y
dat
a
endi
ng
u
p
per
f
o
rm
i
ng dat
a
cl
eani
n
g
pr
ocess
.
Th
e
ope
n s
o
u
r
ce A
P
I i
s
desi
g
n
e
d
usi
n
g ja
va t
h
at
perf
orm
s
ext
r
act
i
on o
f
t
h
e
t
e
r
m
freque
nc
y
as wel
l
as inve
rse
d
o
c
u
m
en
t frequ
en
cy along
with
co
m
p
u
t
atio
n
of sim
u
lat
i
o
n
ti
m
e
. Also
, it sh
ou
ld
b
e
noted
th
at th
e d
a
ta are
hi
g
h
l
y
di
st
ri
bu
t
e
d t
y
pe, whe
r
e t
h
e sy
st
em
is devel
o
pe
d f
o
cu
si
n
g
on
fa
st
er pr
ocessi
n
g
of t
h
e
dat
a
m
i
ni
ng
al
go
ri
t
h
m
s
. The out
c
o
m
e
of t
h
e res
u
l
t
s
hi
gh
l
i
ght
s t
h
at
pr
o
pos
ed sy
st
em
is fo
u
n
d
wi
t
h
i
n
creasi
n
g
si
m
u
l
a
t
i
o
n
ti
m
e
with
th
e i
n
crease of
d
a
taset, and
less
linearity is foun
d
in
th
e
sim
u
lat
i
o
n ti
m
e
.
3.
RESULTS
A
N
D
DI
SC
US
S
I
ON
The p
r
o
p
o
sed
sy
st
em
i
s
desi
gne
d i
n
Jav
a
on 3
2
bi
t
m
achi
n
e. The
pro
p
o
se
d sy
st
em
consi
d
er
s
d
e
sign
ing
a d
a
t
a
b
a
se cap
t
u
r
ed fro
m
m
u
l
tip
le
o
n
lin
e ci
v
ilia
n
’
s g
r
iev
a
n
c
es app
licatio
n
s
. The d
a
taset co
nsists of
1
,
1
5
,000
o
n
line
civ
ilian
s
n
e
twork
i
ng
u
s
ers (Figure
3
)
wh
o are ex
cl
u
s
iv
ely fo
und
to u
s
e
e-g
o
v
e
rnance
gri
e
vances
st
re
am
s i
n
fo
rm
ati
on oc
cu
py
i
n
g ar
ou
n
d
1
5
0
Pet
a
by
t
e
s o
f
dat
a
.
The a
ppl
i
cat
i
o
n de
si
g
n
co
nsi
d
eri
n
g
Evaluation Warning : The document was created with Spire.PDF for Python.
IJECE
ISS
N
:
2088-8708
Mo
del
l
i
ng
of
E
-
G
o
ver
na
nce
F
r
amew
ork f
o
r
Mi
ni
n
g
K
n
ow
l
e
dge
f
r
o
m
M
a
s
s
i
ve Gri
eva
nce
…
(
S
a
ngeet
ha
G)
37
1
fro
m
ex
istin
g
o
n
lin
e civ
ilian’s
g
r
iev
a
n
c
es
n
e
two
r
k
i
ng
fo
ru
m
s
are hug
e
an
d larg
ely h
e
terog
e
n
e
ou
s i
n
typ
e
.
The va
st
num
ber of t
h
e use
r
s
are excl
u
s
i
v
e c
onsi
d
er
s w
ho a
r
e fo
u
nd t
o
w
r
i
t
e
onl
y
t
e
xt
. The sy
st
em
how
eve
r
doe
sn
’t
con
s
i
d
ers any
ot
he
r f
o
rm
at
of dat
a
e.g. P
D
F
,
au
di
o,
vi
deo et
c. A
s
t
h
e st
u
d
y
i
s
for
i
t
s
fi
rst
ki
nd,
w
h
ere
we are
at
t
e
m
p
t
i
ng t
o
pe
rf
or
m
dat
a
m
i
ni
ng o
p
e
r
at
i
o
n
o
n
g
r
i
e
va
nce
d
a
t
a
usi
n
g c
o
n
v
ent
i
o
nal
dat
a
m
i
ni
n
g
techniques
, he
nce, t
h
e focus
is
m
o
re
on
th
e effectiv
e
op
eratio
n
o
f
the mo
d
e
l
witho
u
t
i
n
corp
oratin
g
m
u
ch
o
f
th
e co
m
p
lex
iti
es u
s
ing
d
i
ff
eren
t f
ile f
o
r
m
at
s. A
s
th
e
d
a
ta size is p
r
etty
lar
g
e eno
ugh an
d
m
o
r
e
ov
er
it is
co
llected
fro
m
m
u
ltip
le o
n
line e-go
vern
an
ce g
r
iev
a
n
ce
re
d
r
essal cell sit
e
s, h
e
n
ce th
e
ob
tain
ed
d
a
ta are q
u
ite
m
a
ssi
ve an
d hi
ghl
y
u
n
st
r
u
ct
ur
ed. T
h
e c
o
n
v
e
n
t
i
onal
dat
a
m
i
ni
n
g
al
g
o
ri
t
h
m
i
s
expect
e
d
t
o
fi
n
d
a h
u
g
e ra
nge
o
f
d
i
fficu
lties o
r
co
m
p
u
t
atio
n
a
l
ch
allen
g
es in
d
o
i
n
g
so. Hence, th
e
p
r
o
p
o
s
ed
system
co
n
s
id
ers
p
e
rfo
rm
in
g
the
dat
a
m
i
ni
ng
us
i
ng c
o
nve
nt
i
o
n
a
l
t
echni
ques
o
n
l
a
r
g
e
dat
a
set
s
o
f
e
-
g
o
v
er
na
nce
dat
a
.
Fi
gu
re
3.
Vi
s
u
al
i
zat
i
on o
f
onl
i
n
e ci
t
i
zen I
D
s
A clo
s
er look
i
n
to
t
h
e v
i
su
al
ou
tco
m
es ex
h
i
b
ited
in
Fi
gu
re3
will sh
ow t
h
at
th
e d
a
taset is
main
lyse
mi-
st
ruct
u
r
e
d
an
d pos
sess al
l
t
h
e chal
l
e
ng
es be
f
o
re a
ppl
y
i
n
g
t
h
e con
v
ent
i
onal
dat
a
m
i
ni
ng al
g
o
ri
t
h
m
on t
h
e t
op
of
it. At
p
r
esen
t, th
e an
alysis
is carried
ou
t
o
n
l
y con
s
id
erin
g th
e tex
t
u
a
l
d
a
ta
wh
ich
co
n
s
ist
of alphab
e
ts,
num
erals, spec
ial charecters,
as well as noisy and missi
ng t
e
xt
s t
oo. T
h
er
efo
r
e, a pre
p
ro
cessi
ng i
s
ap
pl
i
e
d t
o
i
d
ent
i
f
y
t
h
e m
i
ssi
ng t
e
xt
usi
n
g st
ri
n
g
-t
hre
s
h
o
l
d
base
d ap
p
r
o
ach, wh
ile noisy d
a
ta are id
en
tified
an
d
eli
m
in
ated
fro
m
th
e list. Th
is step
assi
sts in
m
a
k
i
n
g
th
e
d
a
ta m
o
re reliab
l
e and co
m
p
atib
le to b
e
pro
c
essed un
d
e
r
pr
o
pose
d
dat
a
m
i
ni
ng a
p
p
r
oa
ch
fo
r t
h
e
p
u
r
p
o
se
of
k
n
o
wl
e
d
ge
di
sco
v
ery
.
The ne
xt
st
ep i
s
t
o
per
f
o
rm
cleani
n
g o
p
erat
i
o
n
.
Fi
g
u
re
4 s
h
ows t
h
e com
p
u
t
at
i
on bei
n
g
pe
rf
orm
e
d by
pr
o
pose
d
sy
st
em
t
h
at
fi
nal
l
y
pr
ocess t
h
e
bi
g
dat
a
a
n
d
com
put
e t
o
t
a
l
t
e
rm
, t
e
r
m
to c
h
eck
, TF
(Ter
m
Fre
que
ncy
)
val
u
e, a
nd
I
D
F (
I
nve
rse
Doc
u
m
e
nt
Fre
q
uency
)
val
u
e
fo
r al
l
t
h
e u
s
ers c
o
nsi
d
ere
d
f
r
o
m
t
h
e onl
i
n
e
gri
e
vance
red
r
essal
net
w
or
ki
ng
fo
r
u
m
.
It
i
s
i
n
t
e
rest
i
ng
t
o
k
now th
at ev
en
with
larg
e
dataset, th
e p
r
op
o
s
ed
sy
st
em
i
s
abl
e
t
o
pe
rf
o
r
m
conve
nt
i
o
nal
dat
a
m
i
ni
ng
ope
rat
i
ons
o
n
l
y
o
n
t
h
e sm
al
l
e
r chu
nks
o
f
dat
a
,
w
h
ereas
wh
en
it co
m
e
s
to
larg
er set o
f
data, th
e sim
u
la
tio
n
ti
m
e
is extensively increase
d
, s
h
o
w
i
n
g t
h
e nee
d
of an
effi
ci
ent
p
r
ot
o
c
ol
t
h
at
can pe
rf
orm
t
h
e fast
er com
put
at
i
on
or t
h
e
kn
o
w
l
e
d
g
e di
sc
ove
ry
o
f
t
h
e dat
a
ge
ne
rat
e
d
f
r
o
m
th
e e-
gover
n
an
ce
g
r
iev
a
n
ce’
s on
lin
e
d
i
scu
ssion
fo
ru
m.
Fi
gu
re
4.
G
r
ap
hi
cal
Vi
s
u
al
i
zat
i
on
of
pe
rf
orm
a
nce
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJEC
E V
o
l
.
6, No
. 1, Feb
r
uar
y
20
1
6
:
36
7 – 37
4
37
2
The p
r
o
p
o
sed
sy
st
em
i
s
m
a
i
n
l
y
based on t
h
e feedba
ck ba
s
e
d anal
y
s
i
s
ov
er t
h
e t
e
xt
ual
d
a
t
a
and t
h
ere
f
o
r
e
an
alysis
is
b
e
i
n
g
p
e
rfo
r
m
e
d
to
id
en
tify
th
e p
e
rcen
tag
e
of p
o
s
itiv
e
and
neg
a
tiv
e
feedb
a
ck
o
r
o
p
i
n
i
on
fo
und
in
th
e d
a
taset. Fi
g
u
re
5
h
i
g
h
ligh
t
s th
at th
e
p
r
o
p
o
s
ed
system h
a
s
g
o
t
less
n
e
g
a
tiv
e rev
i
ews an
d
m
o
re
p
o
s
itive
rev
i
ews. A classificatio
n
sch
e
m
e
was co
n
s
tru
c
ted
to
q
u
an
tify th
e ex
ten
t
to
wh
ich
po
sitiv
e an
d
n
e
g
a
tiv
e
e
m
otions
were
expresse
d in
each co
mm
ent. Although
the
conve
n
tional
approaches
(e.g., usa
b
ility
te
st
and
u
s
er i
n
terv
iew) are
u
s
efu
l
for qu
a
litativ
ely k
nowing
th
e
in
teractiv
e
p
r
ob
le
m
s
an
d
u
s
er exp
ectatio
ns o
f
an
o
n
lin
e
g
r
iev
a
nce n
e
twork
foru
m
,
th
ey
are le
ss h
e
lp
fu
l to
id
en
tify who
m
a
y ch
u
r
n
in
th
e fu
t
u
re.
A n
u
m
b
e
r of
research
issu
es and
ch
alle
ng
es facing th
e
realizatio
n
of
u
tilizin
g
d
a
ta m
i
n
i
ng
tech
n
i
q
u
e
s in
on
lin
e st
ud
en
t
net
w
or
k a
n
al
y
s
i
s
co
ul
d
be i
d
e
n
t
i
f
i
e
d as
f
o
l
l
o
ws:
3.
1.
Linkage-B
ase
d
and
Struc
t
u
r
al Anal
ysis
Thi
s
i
s
an
ana
l
y
s
i
s
of t
h
e l
i
nka
ge
be
ha
vi
o
u
r
o
f
t
h
e
o
n
l
i
n
e
gri
e
vance
r
e
dres
sal
net
w
o
r
k
so
as
t
o
ascertain
relevan
t
n
o
d
e
s, lin
ks, co
mm
u
n
ities
an
d
immin
e
n
t
are as o
f
the n
e
twork. Th
e stud
y is fo
und
wit
h
less
l
i
nks as
soci
at
e
d
wi
t
h
m
o
re t
h
an
10
0
use
r
s,
e
v
i
d
e
n
t
l
y
pr
o
v
i
n
g i
n
e
ffect
i
v
e
d
a
t
a
m
i
ni
ng
pr
oc
ess (Fi
g
u
r
e
5
)
.
Fi
gu
re
5.
A
n
al
y
s
i
s
of
Acc
u
ra
cy
i
n
K
n
owl
e
d
g
e
Di
sco
v
ery
3.
2.
Dy
nami
c
An
al
ysi
s
and
St
a
t
i
c
An
al
ysi
s
St
at
i
c
anal
y
s
i
s
suc
h
as i
n
bi
bl
i
o
g
r
ap
hi
c
net
w
or
ks i
s
presum
ed to be
easier to carry
out t
h
an those i
n
streaming net
w
orks. In static analysis, it is pres
um
ed that online e-governa
n
ce st
u
d
e
nt
net
w
or
k c
h
an
ges
gra
d
ual
l
y
ove
r
t
i
m
e
and anal
y
s
i
s
on t
h
e en
t
i
r
e net
w
or
k c
a
n be
d
o
n
e i
n
bat
c
h m
ode.
C
o
n
v
er
sel
y
, d
y
n
am
i
c
anal
y
s
es of st
r
e
am
i
ng net
w
o
r
ks are
very
di
f
f
i
c
ul
t
t
o
carry
out
.
Dat
a
o
n
t
h
ese net
w
or
ks a
r
e ge
nerat
e
d at
hi
g
h
sp
eed
and
cap
a
city. Dyn
a
m
i
c
an
alyses of th
ese n
e
two
r
k
s
are o
f
ten
in
th
e area of in
teracti
o
n
s
b
e
t
w
een
en
tities.
The
o
u
t
c
om
e of t
h
e
st
u
d
y
s
h
o
w
s m
o
re si
m
u
l
a
t
i
on t
i
m
e l
eadi
ng t
o
ove
r
h
ea
d.
Fi
gu
re 6.
A
n
al
y
s
i
s
of Si
m
u
l
a
ti
on Ti
m
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
Mo
del
l
i
ng
of
E
-
G
o
ver
na
nce
F
r
amew
ork f
o
r
Mi
ni
n
g
K
n
ow
l
e
dge
f
r
o
m
M
a
s
s
i
ve Gri
eva
nce
…
(
S
a
ngeet
ha
G)
37
3
The
o
u
t
c
om
e sho
w
s t
h
at
a
d
o
p
t
i
o
n
o
f
c
o
n
v
e
n
t
i
onal
dat
a
m
i
ni
ng
t
ech
ni
q
u
e c
a
n
be
defi
ni
t
e
l
y
use
d
f
o
r
extracting unique knowledge.
The res
u
lts shown in Figure 6 also hi
gh
lights that accurac
y
in
analysis proces
s
is qu
ite im
p
r
o
v
i
ng
with
i
n
crease of
d
a
taset fro
m
e-
gove
rna
n
ce a
p
plications. He
nce,
it can
be see
n
tha
t
id
en
tificatio
n of resou
r
ces, tech
no
log
y
infrast
ru
ct
u
r
e is
t
h
ere
i
n
co
n
v
ent
i
on
al
dat
a
m
i
ni
ng
al
go
ri
t
h
m
.
Ho
weve
r
,
owi
n
g to m
a
ssive size of
dat
a
the acc
uracy
i
s
ar
ou
n
d
5
7
%
, w
h
i
c
h
can
be f
u
rt
he
r m
o
re en
hance
d
i
n
fut
u
re.
There i
s
a g
o
od sc
o
p
e o
f
o
p
t
i
m
i
zat
i
on pri
n
ci
pl
e o
v
er c
o
nve
nt
i
o
nal
dat
a
base t
o
per
f
o
r
m
effect
i
v
e m
i
ni
ng
ope
rat
i
o
n.
4.
CO
NCL
USI
O
N
The propose
d syste
m
discusses abou
t the fra
m
ework that evaluates th
e
extent of effec
tiveness
of
con
v
e
n
t
i
onal
d
a
t
a
m
i
ni
ng al
g
o
r
i
t
h
m
s
on l
a
rg
e dat
a
capt
u
re
d f
r
om
e-g
ove
rna
n
ce
gri
e
v
a
n
ce red
r
essal
d
a
t
a
i
n
m
u
l
tip
le o
n
lin
e resou
r
ces av
ailab
l
e. Th
e ou
tco
m
e o
f
th
e stu
d
y
sh
ows
h
i
gher si
m
u
latio
n
time,
m
o
re o
v
e
rh
ead,
and inacc
urac
y in
know
ledge discove
r
y process.
Th
ere
f
ore, we are successfully
exhibiting the fa
ct that
con
v
e
n
t
i
onal
d
a
t
a
m
i
ni
ng al
g
o
ri
t
h
m
s
canno
t
be di
rect
l
y
appl
i
cabl
e
t
o
B
i
g Dat
a
fo
r pe
rf
orm
i
ng k
n
o
w
l
e
d
g
e
d
i
scov
er
ed pr
ocess.
H
e
nce, t
h
e co
r
e
f
i
n
d
i
ng
s
o
f
th
e
study ar
e as fo
llow
s
e.g. i) th
e
ex
istin
g and up
co
m
i
n
g
appl
i
cat
i
o
ns o
f
e-g
ove
r
n
ance
fram
e
wor
k
wi
l
l
l
ead t
o
gene
r
a
t
i
on o
f
m
a
ssive v
o
l
u
m
e
of t
h
e dat
a
t
h
at
re
qui
res
d
a
ta an
alytics, ii) th
e ex
isting
d
a
ta an
alytics to
o
l
(o
r dat
a
m
i
ni
ng a
p
p
r
oa
ches) a
r
e
not
di
rect
l
y
appl
i
c
abl
e
t
o
su
ch
m
a
ssiv
e
d
a
tab
a
se
o
w
i
n
g
to
un
stru
ctured
o
r
sem
i
-stru
c
t
u
red
fo
rm
at o
f
th
e datab
a
se, iii) th
e
ex
istin
g
datamining tec
hni
que ca
n
be
applicable
t
o
massive data a
l
so provide
d
if
accurate
pre
p
roces
sing is done t
o
con
v
e
r
t
unst
r
u
c
t
u
re
d or sem
i
-st
r
uct
u
re
d
dat
a
t
o
st
ruct
u
r
ed
one, i
v
) dat
a
m
i
ni
ng base
d
on
feed
bac
k
s
y
st
em
co
u
l
d
b
e
h
i
gh
l
y
en
han
c
ed
u
s
i
n
g op
tim
iza
tio
n
tech
n
i
q
u
e
s in
fu
tu
re.
Ou
r fu
tu
re wo
rk will
b
e
i
n
th
e
d
i
rectio
n
of
prese
n
t
i
n
g a
d
e
si
gn
o
f
c
o
l
l
a
b
o
rat
i
v
e
net
w
o
r
k t
h
at
c
a
n
sha
r
e g
r
i
e
va
nce i
n
f
o
rm
at
i
on o
n
a
cl
ou
d.
The
p
r
o
pos
ed
syste
m
h
a
s fo
llo
wi
n
g
b
e
n
e
fit fo
r th
e
d
ecision
mak
e
rs an
d civilian
s
:
They
d
o
n
o
t
h
a
ve t
o
deal
wi
t
h
t
h
e het
e
r
o
ge
neo
u
s a
nd s
p
o
r
adi
c
i
n
fo
rm
ation
gene
rat
e
d
b
y
vari
o
u
s st
at
e-
level com
puterization
projec
ts as they can access
c
u
rrent data with a high granularity from
the
in
fo
rm
atio
n
warehou
se.
They
ca
n t
a
ke
m
i
cro-l
e
vel
de
ci
si
ons i
n
a t
i
m
el
y
m
a
nner
wi
t
h
o
u
t
t
h
e
nee
d
t
o
depe
n
d
on
t
h
ei
r IT
st
aff
.
They
ca
n o
b
t
a
i
n
easi
l
y
de
ci
phe
rabl
e a
n
d c
o
m
p
rehe
ns
i
v
e i
n
f
o
rm
ati
on
wi
t
h
o
u
t
t
h
e nee
d
t
o
us
e
sophisticated t
ools
.
They can pe
rform
extensive analysis
o
f
stored
d
a
ta to
prov
id
e an
swers to
th
e exh
a
u
s
ti
v
e
qu
eries to
th
e
ad
m
i
n
i
strativ
e cadre.
Th
is help
s th
em
to
fo
rm
u
l
ate
m
o
re effectiv
e strat
e
g
i
es an
d po
li
cies fo
r citizen
facilitatio
n
.
They are t
h
e
ultimate benefic
i
aries of the
new
polic
i
e
s f
o
rm
ul
at
ed by
t
h
e deci
si
o
n
m
a
kers
an
d
pol
i
c
y
p
l
ann
e
r
'
s ex
tensiv
e an
alysis on
p
e
r
s
on
an
d lan
d
-
r
e
lated data.
Th
ey can v
i
ew frequ
en
tly asked
q
u
e
ries who
s
e
resu
lts
will alread
y b
e
there in
t
h
e
d
a
tab
a
se an
d will
b
e
im
m
e
di
at
el
y
show
n t
o
t
h
e
u
s
er
savi
ng
t
h
e t
i
m
e re
qui
re
d
f
o
r
pr
ocessi
ng
.
They ca
n
have
easy access to the
Go
ve
rnm
e
nt policies
of the state.
The
we
b acces
s to
Inform
atio
n
Ware
house
e
n
ables
them
to access the
publ
ic dom
ain data
from
anywhe
re
.
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NC
ES
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e
z
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t
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r
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rvice Orien
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.
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.
BIOGRAP
HI
ES OF
AUTH
ORS
Sangeeth
a
Govi
nda is working
a
s
Assistant Professo
r, Departm
e
n
t
of MCA,
Adar
sh Institute
of
M
a
nagem
e
nt an
d Inform
ation Techno
log
y
, Ba
ngalore
. S
h
e h
a
s
got 10
year
s
of teach
ing
experience. She
has obtained
Bach
elor
of Science from Bang
alor
e University
in the
y
e
ar 2000
.
She studied Masters of Computer Applicati
on
from IGNOU and was awarded in th
e
y
e
ar
2006.She obtain
e
d Bach
elor of
Education in
20
08. In 2014 did
Master of Philosoph
y
from
Bharath
i
ar Univ
ers
i
t
y
, Coim
bato
re. Now s
h
e is
a P
h
.D. s
t
udent
3rd
y
e
ar of CS
E at Bharath
i
ar
University
, Co
imbatore, Ind
i
a.
She has author
ed
one (1) Textb
ook. She has pu
blished pap
e
rs in
both nation
a
l
an
d intern
ation
a
l
conferences and 2
re
s
earch
papers
in Inte
rn
ation
a
l Journals.
Now
currently
workin
g in B
a
ngalo
re, I
ndia.
Dr. L. Manjun
atha R
a
o is
working as Profes
s
o
r and H
ead, D
e
partment of M
C
A, Dr. AIT,
Bangalor
e
. He h
a
s got 25
y
e
ars of teaching
exp
e
rien
ce. He did
his Bachelor of
Science from
Bangalor
e
Univ
ersity
in th
e
y
e
ar 1990. He St
udied Masters
of Computer Application from
Madhurai Kamaraj University
and was awarde
d in the
y
e
ar 1999. In 2002 d
i
d Master of
Philosoph
y
from Mononmanium Sundaranar Universi
ty
. He has
awarded Ph.D from Vinay
a
ka
Mission University
, Tamil Nadu. He has publis
hed research
papers in both national and
intern
ation
a
l Jou
r
nals and
h
a
s au
thored 2
textboo
ks.
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