A00-2023 |
obtain timing measurements for the
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search algorithm
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alone . We estimate that roughly
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A83-1021 |
top of the inverted file and the
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search algorithms
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. it accepts terms , search modifiers
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A00-1044 |
training data , modeling , and
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search algorithm
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for errorful input as we do for
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A00-2041 |
programming is an opportunistic
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search algorithm
|
used for constructing computer
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C00-1068 |
and their scores by using A *
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search algorithm
|
. Using the scores of these N-best
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A97-1026 |
essay , the scoring program uses a
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searching algorithm
|
RESULTS Table 1 shows the results
|
A94-1037 |
and a dynamicprogramming based
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search algorithm
|
. After an overview of our approach
|
C00-1070 |
end node ( $ / $ ) . The Viterbi
|
search algorithm
|
( Forney , 1973 ) , which has
|
A88-1033 |
point list is completed , the
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search algorithm
|
is applied as described above
|
C00-2091 |
are defined . We bast the proof
|
search algorithm
|
corresponding to the generation
|
C00-2123 |
order to achieve an efficient
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search algorithm
|
. A search restriction especially
|
C00-2098 |
through the lattice using an A * -
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search algorithm
|
. This is similar to the work
|
C00-1068 |
maximum likelihood is obtained by a
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search algorithm
|
. A score of sentence derived
|
C00-2110 |
et al. proposed a backward beam
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search algorithm
|
( analyze a sentence froln the
|
C00-1081 |
" wn = w ( T ) . 3.2 Solution
|
Search Algorithm
|
As shown in formula ( 3 ) , our
|
C00-2151 |
required by the non-iucremental
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search algorithm
|
is given as the white bar . The
|
A00-2023 |
solution . A capped N-best heuristic
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search algorithm
|
on the other hand has complexity
|
A00-2010 |
are defined . We base the proof
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search algorithm
|
corresponding to the generation
|
C00-2109 |
description . <title> Backward Beam
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Search Algorithm
|
for Dependency Analysis of Japanese
|
C00-2110 |
sentence length using a backward
|
search algorithm
|
. Recently , a mnnber of research
|