NLP for CP
Addressing Constraint Programming with Natural Language Processing
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Correct
predictions are in
blue
. If we detect only a subset of a labelled sentence, we highlight the caught part as
blue
, the missing part
light blue.
False positives
are in
green
and
false negatives
are in
red
.
Problem 114 (Subgraph Isomorphism) — Constraint detection
A
subgraph
isomorphism
problem
-LRB-
SIP
-RRB-
between
a
pattern
graph
Gp
=
-LRB-
Np
,
Ep
-RRB-
and
a
target
graph
Gt
=
-LRB-
Nt
,
Et
-RRB-
consists
in
deciding
whether
Gp
is
isomorphic
to
some
subgraph
of
Gt
.
More
precisely
,
one
should
find
an
injective
function
$
f
:
Np
\
to
Nt
$
that
associates
a
different
node
of
the
target
graph
with
every
node
of
the
pattern
graph
and
that
matches
edges
of
the
pattern
graph
,
i.e.
,
$
\
forall
-LRB-
u
,
v
-RRB-
in
Np
\
times
Np
,
-LRB-
u
,
v
-RRB-
\
in
Ep
\
Rightarrow
-LRB-
f
-LRB-
u
-RRB-
,
f
-LRB-
v
-RRB-
-RRB-
\
in
Et
$
.
Note
that
the
subgraph
is
not
necessarily
induced
so
that
two
pattern
nodes
that
are
not
linked
by
an
edge
may
be
matched
to
target
nodes
which
are
linked
by
an
edge
.
Problem 114 (Subgraph Isomorphism) — Detection of the decisions and objects to be modeled
A
subgraph
isomorphism
problem
-LRB-
SIP
-RRB-
between
a
pattern
graph
Gp
=
-LRB-
Np
,
Ep
-RRB-
and
a
target
graph
Gt
=
-LRB-
Nt
,
Et
-RRB-
consists
in
deciding
whether
Gp
is
isomorphic
to
some
subgraph
of
Gt
.
More
precisely
,
one
should
find
an
injective
function
$
f
:
Np
\
to
Nt
$
that
associates
a
different
node
of
the
target
graph
with
every
node
of
the
pattern
graph
and
that
matches
edges
of
the
pattern
graph
,
i.e.
,
$
\
forall
-LRB-
u
,
v
-RRB-
in
Np
\
times
Np
,
-LRB-
u
,
v
-RRB-
\
in
Ep
\
Rightarrow
-LRB-
f
-LRB-
u
-RRB-
,
f
-LRB-
v
-RRB-
-RRB-
\
in
Et
$
.
Note
that
the
subgraph
is
not
necessarily
induced
so
that
two
pattern
nodes
that
are
not
linked
by
an
edge
may
be
matched
to
target
nodes
which
are
linked
by
an
edge
.
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