SEMANTIC CONFLICT DETECTION IN META-DATAcobweb.cs.uga.edu/~budak/thesis/gk_talk.pdf ·...
41
SEMANTIC CONFLICT DETECTION IN META-DATA A RULE-BASED APPROACH KARTHIKEYAN GIRILOGANATHAN ADVISOR: Dr. I. BUDAK ARPINAR COMMITTEE: Dr. AMIT P. SHETH Dr. KHALED M. RASHEED
Transcript of SEMANTIC CONFLICT DETECTION IN META-DATAcobweb.cs.uga.edu/~budak/thesis/gk_talk.pdf ·...
SEM
AN
TIC
CON
FLIC
T D
ETE
CTIO
N IN
ME
TA-D
ATA
A
RU
LE-B
ASE
D A
PPRO
ACH
KA
RTH
IKE
YAN
GIR
ILO
GA
NA
THA
N
AD
VIS
OR
: D
r. I.
BU
DA
K A
RPI
NA
RC
OM
MIT
TEE
: Dr.
AM
IT P
. SH
ETH
Dr.
KH
ALE
D M
. RA
SHE
ED
Intro
duct
ion
Mas
sive
am
ount
of d
ata
is a
vaila
ble
on th
e W
ebA
bilit
y to
ann
otat
e, e
xtra
ct, a
nd q
uery
sem
antic
met
a-da
ta h
as
incr
ease
d:S
WE
TO (S
eman
tic W
eb T
echn
olog
y E
valu
atio
n O
ntol
ogy)
:po
pula
ted
with
ove
r 800
,000
ent
ities
and
1.5
mill
ion
expl
icit
rela
tions
hips
bet
wee
n th
em in
RD
F or
OW
LFr
eedo
m (S
emag
ix):
uses
SW
ETO
and
oth
er d
omai
n on
tolo
gies
to s
eman
tical
ly
anno
tate
mill
ions
of d
ocum
ents
or W
eb p
ages
Web
Fou
ntai
n (IB
M):
anno
tate
d an
d di
sam
bigu
ated
dat
a fro
m o
ver a
billi
on
docu
men
ts
Intr
oduc
tion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Evo
lutio
n of
Met
a-D
ata
[She
th20
03]
Intr
oduc
tion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Nex
t gen
erat
ion
tool
s w
ill fo
cus
on a
ctio
nabl
e in
form
atio
n (w
ith a
ssoc
iate
d so
urce
s an
d su
ppor
ting
evid
ence
) fro
m
exis
ting
(met
a-)d
ata
Con
cern
s ab
out u
sage
of m
eta-
data
Hig
h qu
ality
(i.e
., re
liabl
e, a
ccur
ate,
and
trus
twor
thy)
sem
antic
m
eta-
data
Ent
ity d
isam
bigu
atio
nIn
cons
iste
ncy
chec
king
in O
WL
Con
flict
det
ectio
n
Met
a-D
ata
Conc
erns
Intr
oduc
tion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Mot
ivat
ing
Fact
ors
“Rep
rese
ntin
g, id
enti
fyin
g, d
isco
veri
ng, v
alid
atin
g, a
nd
expl
oiti
ng c
ompl
ex r
elat
ions
hips
are
impo
rtan
t is
sues
rel
ated
to
rea
lizin
g th
e fu
ll po
wer
of t
he S
eman
tic
Web
, and
can
hel
p cl
ose
the
gap
betw
een
high
ly s
epar
ated
info
rmat
ion
retr
ieva
lan
d de
cisi
on-m
akin
gst
eps”
[She
th, A
rpin
ar&
Kash
yap
2003
]
“The
Web
is d
ecen
tral
ized
, allo
wing
any
one
to s
ay a
nyth
ing.
As
a re
sult
, dif
fere
nt v
iewp
oint
sm
ay b
e co
ntra
dict
ory,
or
even
fa
lse
info
rmat
ion
may
be
prov
ided
. In
orde
r to
pre
vent
age
nts
from
com
bini
ng in
com
pati
ble
data
or
from
tak
ing
cons
iste
nt
data
and
evo
lvin
g it
into
an
inco
nsis
tent
sta
te, i
t is
impo
rtan
tth
at in
cons
iste
ncie
sca
n be
det
ecte
d au
tom
atic
ally
”[W
3C
2004
]
“…th
ese
prob
lem
s m
anif
est
them
selv
es in
var
ious
way
s,
incl
udin
g po
or r
ecal
l of
avai
labl
e re
sour
ces
and
inco
nsis
tenc
yof
sea
rch
resu
lts.
The
y ar
ise
due
to e
rror
s, o
mis
sion
san
d am
bigu
itie
sin
the
met
adat
a…”[
Curr
ier
& Ba
rton
200
3]
Intr
oduc
tion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
John
Cla
ura
Bill
Mar
y
fath
erO
fm
arrie
dTo
mot
herO
f
fath
erO
f
mar
riedT
o
fath
erin
Law
Of
CO
NFL
ICT
Sem
antic
Con
flict
Iden
tific
atio
n
Intr
oduc
tion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Conf
lict i
llust
ratio
n th
roug
h Si
mpl
ifica
tion
CO
NFL
ICT
Intr
oduc
tion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Met
aDat
aS
tore
Var
ious
alg
orith
ms
for s
eman
tic a
naly
tics
Que
ry in
terfa
ce
Mot
ivat
ing
Scen
ario
EX
TRA
CTO
RS
(F
reed
om)
Sem
DIS
SW
ETO
Intr
oduc
tion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Out
line
Con
flict
type
s an
d de
finiti
ons
Sim
plifi
catio
n pr
oces
sS
yste
m a
rchi
tect
ure
Exp
erim
enta
l res
ults
Con
clus
ion
and
futu
re w
ork
Intr
oduc
tion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
‘dam
l:una
mbi
guou
s’ o
r ‘o
wl:i
nver
seFu
nctio
nal-
Pro
perty
’ vio
latio
n
Prop
erty
Ass
ertio
n Co
nflic
ts
‘dam
l:uni
que’
or
‘ow
l:Fun
ctio
nal-P
rope
rty’
viol
atio
n
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Prop
erty
Ass
ertio
n Co
nflic
ts
‘asy
mm
etric
’ pro
perty
vi
olat
ion
‘dis
join
t’ pr
oper
ty
viol
atio
n
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Clas
s Ass
ertio
n Co
nflic
ts
Cla
sses
c1
and
c2 a
re
‘dam
l:dis
join
t’ or
‘o
wl:d
isjo
int’
Cla
sses
‘Citi
zen’
and
‘Im
mig
rant
’ are
‘d
aml:d
isjo
int’
or
‘ow
l:dis
join
t’
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Clas
s Ass
ertio
n Co
nflic
ts
Cla
ss ‘E
mpl
oyee
’ has
a
OW
L or
DA
ML
rest
rictio
n ‘m
axC
ardi
nalit
y’ o
f ‘1’
on
a re
latio
n ‘h
asD
esig
natio
n’
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Stat
emen
t Ass
ertio
n Co
nflic
ts
We
wan
t to
say
that
a
pers
on c
anno
t be
a su
perio
r and
a fr
iend
to
“Joh
n” a
t the
sam
e tim
e.
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Non
-Ass
ertio
nalC
onfli
cts
Eith
er th
e su
bjec
t or t
he o
bjec
t alo
ne is
diff
eren
t bet
wee
n tw
o R
DF
tripl
es.
Sub
ject
ive
Con
flict
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Con
stra
ints
sup
plie
d by
an
expe
rt (e
.g.,
pers
on(x
) ca
n ne
ver
do
actio
n(y)
)E
Con
stra
ints
ex
pres
sed
in
an
onto
logy
(e
.g.,
the
prop
erty
‘b
iolo
gica
lMot
her’
is u
niqu
e)U
The
resu
lt of
sim
plifi
catio
n(S
(T)
s)s
A fu
nctio
n de
notin
g th
e pr
oces
s of
sim
plifi
catio
nS
A s
et o
f trip
les
T
Two
sets
of t
riple
s T1
and
T2 a
re sa
id to
be
in c
onfli
ctif
thei
r sim
plifi
catio
nsS(
T1)
s1 a
nd S
(T2)
s2 a
re m
utua
lly
non-
agre
eabl
e.
Conf
lict D
efin
ition
s
Two
sim
plifi
catio
nss1
and
s2 a
re m
utua
lly n
on-a
gree
able
if ta
ken
toge
ther
they
are
in v
iola
tion
of U
or E
.
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Will
iam
sC
hris
Rep
ublic
anPa
rtyvo
tedF
orm
embe
rOf
supp
orte
rOf
Sim
plifi
catio
n Ty
pes
An
RD
F tri
ple
is tr
ivia
lly a
sim
plifi
catio
nbe
caus
e it
is
the
mos
t bas
ic p
iece
of k
now
ledg
eC
ompo
sitio
n of
rela
tions
lead
s to
sim
plifi
catio
n
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Com
posit
ion
of R
elatio
nsC
onsi
der a
set o
f Trip
les T
,Le
t E
-se
t of e
ntiti
es
P-
set o
f rel
atio
ns
Then
, E=
{e1,
e2.
.. en
}P
= {p
1, p
2...
pm}.
Le
tC
-se
t of o
rder
ed re
latio
n tu
ples
that
can
be
com
pose
dto
a si
ngle
rela
tion
R-
set o
f rel
atio
ns o
btai
ned
by su
bstit
utin
g th
e co
mpo
sed
rela
tion
for t
he c
ompo
sabl
ere
latio
ns.
Then
, C=
{(p1
, pk)
, ...,
(pa,
pb,
pc,
...)}
. R
={r
1, r2
... rn
}, w
here
r1, r
2...
rnar
e re
sults
of
the
com
posi
tion.
The
tripl
e (
The
tripl
e ( e
ieirkrk
ejej) i
s a
) is
a si
mpl
ifica
tion
sim
plifi
catio
nif if
rkrk∈∈
R a
nd
R a
nd e
i,ej
ei,e
j ∈∈E
.E
.
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Stat
emen
t Sim
plifi
catio
n
Ther
e co
uld
be b
ackg
roun
d kn
owle
dge
base
d si
mpl
ifica
tions
of t
he fo
rm:
stat
emen
t 1∧
stat
emen
t 2∧
… st
atem
ent n→
sta
tem
ent t
In th
is c
ase
stat
emen
t tis
a s
impl
ifica
tion.
This
type
of s
impl
ifica
tion
will
dep
end
on e
xper
t kn
owle
dge.
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Stat
emen
t Sim
plifi
catio
n
Imm
igra
ntIm
mig
rant
Fina
ncia
lOrg
aniz
atio
n
Judi
cial
Org
aniz
atio
n
Bus
ines
sOrg
aniz
atio
n
Per
son
mul
tiple
Dep
osits
asso
ciat
ed
owne
r
wor
ks
unde
rInve
stig
atio
n
Mon
eyLa
unde
ring
susp
ecte
d
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Def
inin
g St
atem
ent S
impl
ifica
tion
Rules
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Rule
ML
(Ove
rvie
w)
Exp
lore
rule
sys
tem
s su
itabl
e fo
r the
Web
The
synt
ax (i
n X
ML
and
RD
F fo
rm)
Sem
antic
sTr
acta
bilit
y/ef
ficie
ncy
Tran
sfor
mat
ion
Com
pila
tion
Ena
ble
infe
renc
ing
on W
eb d
ata
& in
terc
hang
e of
rule
s be
twee
n in
telli
gent
sys
tem
s (o
ntol
ogy
inte
grat
ion
etc.
)W
e us
e R
uleM
LA
ny in
fere
nce
engi
ne th
at u
nder
stan
ds R
uleM
Lca
n ev
alua
te o
ur ru
les.
W
e do
not
nee
d to
thin
k ab
out r
epre
sent
atio
n an
d tra
nsla
tion.
http
://w
ww
.rule
ml.o
rg/
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Our
Rep
rese
ntat
ion
of a
n RD
F tri
ple
<sub
ject
><pr
oper
ty><
obje
ct>
Sta
tem
ent(x
)S
ubje
ct(x
,sub
ject
)P
rope
rty(x
,pro
perty
)O
bjec
t(x,o
bjec
t)
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
ifst
atem
ent(
x) a
nd s
tate
men
t(y)
and
su
bjec
t(x,
a) a
nd r
elat
ion(
x,re
l1) a
nd
obje
ct(x
,b) a
nd s
ubje
ct(y
,a) a
nd
rela
tion
(y,r
el2)
and
obj
ect(
y,b)
and
disj
oint
(rel
1,re
l2)
then
conf
lict(
x,y)
Conf
lict R
ules
Can
be
clas
sifie
d as
Inte
grity
Con
stra
int R
ules
.
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Sim
plifi
catio
n Ru
les
Can
be
clas
sifie
d as
Pro
duct
ion
Rul
es
ifst
atem
ent(
x) a
nd s
tate
men
t(y)
and
subj
ect(
x,a)
and
rel
atio
n(x,
rel1)
and
obje
ct(x
,b) a
nd s
ubje
ct(y
,a) a
nd
rela
tion
(y,r
el2)
and
obj
ect(
y,b)
then
newS
tate
men
t(a,
rel
3, b
)
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Relat
ions
hip
Ont
olog
y
Rel
atio
ns a
re a
t the
hea
rt of
sem
antic
Web
[S
heth
, Arp
inar
& K
ashy
ap20
03]
Rel
atio
ns a
mon
g re
latio
ns n
eed
to b
e sp
ecifi
edH
iera
rchy
of r
elat
ions
is s
imila
r to
a ta
xono
my
Just
as
we
have
mov
ed fr
om ta
xono
my
to
onto
logy
the
idea
is to
hav
e an
ont
olog
y fo
r re
latio
ns a
lso.
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Relat
ions
hip
Ont
olog
y
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Edi
ting/
Popu
latin
g th
e Re
latio
nshi
p O
ntol
ogy
Intro
duct
ion
Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
eR
esul
tsC
oncl
usio
n
Tem
plat
e Ba
sed
Rule
Tra
nsfo
rmat
ion
if st
atem
ent(x
) and
stat
emen
t(y) a
ndsu
bjec
t(x,a
) and
rela
tion(
x,re
l1)a
nd o
bjec
t(x,b
) and
su
bjec
t(y,a
) and
rela
tion(
y,re
l2)a
nd o
bjec
t(y,b
) and
di
sjoi
nt(r
el1,
rel2
)the
n co
nflic
t(x,y
)
disj
oint
(http
://fo
o.co
m/te
st#l
ikes
, ht
tp://
foo.
com
/test
#hat
es)
Tran
sfor
m
if st
atem
ent(x
) and
stat
emen
t(y) a
nd
subj
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latio
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y, h
ttp://
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bjec
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disj
oint
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o.co
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, http
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ates
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duct
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Con
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Typ
esSi
mpl
ifica
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Arc
hite
ctur
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oncl
usio
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Sem
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Typ
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Arc
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Find
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Find
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Find
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Sim
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Con
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e st
atem
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to tr
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Con
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FO
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ules
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Whi
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Con
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Rul
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List
of S
tate
men
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at a
re in
con
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Der
ivat
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avai
labl
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r con
flict
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eriv
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aila
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if st
mts
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tern
ally
Intro
duct
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Con
flict
Typ
esSi
mpl
ifica
tion
Arc
hite
ctur
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oncl
usio
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Man
dara
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cla
ss li
brar
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r ded
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les
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ot a
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inte
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Bas
ed o
n ba
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asy
inte
grat
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eb s
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and
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es s
peci
fied
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uleM
LJe
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ietri
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asse
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nive
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, New
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list
of c
ontri
buto
rs a
vaila
ble
at h
ttp://
man
dara
x.so
urce
forg
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t/
ww
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anda
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org
Intro
duct
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Con
flict
Typ
esSi
mpl
ifica
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Arc
hite
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oncl
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Kno
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and
Rul
es
Intro
duct
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Con
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Typ
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mpl
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Arc
hite
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oncl
usio
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Resu
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Intro
duct
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Con
flict
Typ
esSi
mpl
ifica
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Arc
hite
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oncl
usio
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Stat
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Intro
duct
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Con
flict
Typ
esSi
mpl
ifica
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Arc
hite
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oncl
usio
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Perf
orm
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Eva
luat
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Intro
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Typ
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Arc
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oncl
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riple
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7.030853263
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020
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No
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Intro
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Typ
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mpl
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Arc
hite
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oncl
usio
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Conc
lusio
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In th
is w
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we
have
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efin
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onfli
cts
in s
eman
tic m
eta-
data
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cl
assi
fied
them
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iscu
ssed
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conf
licts
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how
n th
e us
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rela
tions
bet
wee
n re
latio
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si
mpl
ify th
e tri
ples
and
iden
tify
conf
licts
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emon
stra
ted
the
appl
icab
ility
of t
he a
ppro
ach
over
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mite
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ta s
et u
sing
a p
roto
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Intro
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Con
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Typ
esSi
mpl
ifica
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Arc
hite
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usio
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Futu
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Our
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clud
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velo
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cala
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tech
niqu
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r lar
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ata
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Inve
stig
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etho
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rm to
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echa
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for e
xpre
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valu
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nd a
djus
ting
trust
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amic
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ed o
n co
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Intro
duct
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Con
flict
Typ
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mpl
ifica
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Arc
hite
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oncl
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Que
stio
ns?
Than
k Y
ou
