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 111 (Maximum Clique Problem) — Constraint detection
A
clique
of
a
graph
G
=
-LRB-
X
,
E
-RRB-
is
a
subset
V
of
X
,
such
that
every
two
nodes
in
V
are
joined
by
an
edge
of
E
.
The
maximum
clique
problem
consists
of
finding
$
\
omega
-LRB-
G
-RRB-
$
,
the
largest
cardinality
of
a
clique
.
Problem 111 (Maximum Clique Problem) — Detection of the decisions and objects to be modeled
A
clique
of
a
graph
G
=
-LRB-
X
,
E
-RRB-
is
a
subset
V
of
X
,
such
that
every
two
nodes
in
V
are
joined
by
an
edge
of
E
.
The
maximum
clique
problem
consists
of
finding
$
\
omega
-LRB-
G
-RRB-
$
,
the
largest
cardinality
of
a
clique
.
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