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 106 (Temporal Knapsack Problem) — Constraint detection
In
the
TKP
a
resource
allocator
is
given
bids
for
portions
of
a
timeshared
resource
-
such
as
CPU
time
or
communication
bandwidth
-
or
a
sharedspace
resource
-
such
as
computer
memory
,
disk
space
,
or
equivalent
rooms
in
a
hotel
that
handles
block-booking
.
Each
bid
specifies
the
amount
of
resource
needed
,
the
time
interval
throughout
which
it
is
needed
,
and
a
price
offered
for
the
resource
.
The
resource
allocator
has
the
problem
of
selecting
a
subset
of
the
bids
such
that
in
each
time
interval
the
demand
of
the
selected
bids
does
not
exceed
the
capacity
of
that
time
interval
,
and
the
total
price
obtained
is
maximised
.
Problem 106 (Temporal Knapsack Problem) — Detection of the decisions and objects to be modeled
In
the
TKP
a
resource
allocator
is
given
bids
for
portions
of
a
timeshared
resource
-
such
as
CPU
time
or
communication
bandwidth
-
or
a
sharedspace
resource
-
such
as
computer
memory
,
disk
space
,
or
equivalent
rooms
in
a
hotel
that
handles
block-booking
.
Each
bid
specifies
the
amount
of
resource
needed
,
the
time
interval
throughout
which
it
is
needed
,
and
a
price
offered
for
the
resource
.
The
resource
allocator
has
the
problem
of
selecting
a
subset
of
the
bids
such
that
in
each
time
interval
the
demand
of
the
selected
bids
does
not
exceed
the
capacity
of
that
time
interval
,
and
the
total
price
obtained
is
maximised
.
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