C94-1032 |
morphological analyzers use rule-based
|
heuristic searches
|
. They usually use a connectivity
|
C86-1067 |
possible paths , the following
|
heuristic search
|
method is adopted . First , a
|
D12-1046 |
tuned on development data using a
|
heuristic search
|
. Parameters that achieved the
|
C69-2901 |
nondeterministic procedures employing
|
heuristic search
|
and evaluation . The rules employed
|
C04-1166 |
described in ( Max , 2003b ) . A
|
heuristic search
|
procedure in the space of content
|
D09-1007 |
framing CKY item generation as a
|
heuristic search
|
prob - lem . Once we recognize
|
C90-3040 |
credit , Ng and Mooney discuss a
|
heuristic search
|
mechanism that is guided by coherence
|
D09-1007 |
we do better ? Why not perform
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heuristic search
|
directly on this search space
|
D09-1007 |
heuristics to the nodes and run a
|
heuristic search
|
protocol , say A * , on this
|
C00-2151 |
optimization . Both complete and
|
heuristic search
|
methods can be eml ) loyed to
|
A88-1021 |
" business " along any path of
|
heuristic searching
|
. Therefore we prefer to attach
|
D09-1007 |
nonterminals . A key benefit of the
|
heuristic search
|
viewpoint is that it is well
|
D09-1070 |
affixes . This typically involves
|
heuristic search
|
procedures and calibrating multiple
|
D12-1051 |
2010 ) . However , the greedy
|
heuristic search
|
algorithms only explore a fraction
|
D09-1070 |
parameters that need to be set , and
|
heuristic search
|
procedures are crucial for their
|
D09-1007 |
given span . 3 Item Generation as
|
Heuristic Search
|
Refer again to the example in
|
D10-1091 |
technique , which is to guide a
|
heuristic search
|
in an hypergraph representing
|
D09-1007 |
number of nodes visited by the
|
heuristic search
|
, the average time to decode
|
D12-1051 |
is natural to use some greedy
|
heuristic search
|
algorithms for inference in some
|
A00-2023 |
optimal solution . A capped N-best
|
heuristic search
|
algorithm on the other hand has
|