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accuracy and cover - age . We can do
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graph pruning
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simply by choosing to use different
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D12-1076 |
decided by SCAN . The semantic
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graph pruning
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threshold is set to 0.27 tuned
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W07-0721 |
experiment with several ways of
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graph pruning
|
. Addition - ally , for each
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N10-1108 |
redundant patterns are removed via a
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graph pruning
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algorithm . In experiments on
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W07-0721 |
n-gram length greater than 5 . 5.4
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Graph pruning
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The more complex is the reordering
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W07-0721 |
, we experiment with different
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graph pruning
|
which guarantees the translation
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N12-1051 |
task-specific algorithms such as
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graph pruning
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, edge weighting , and so on
|
J13-3007 |
taxon - omy , we perform a step of
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graph pruning
|
, as described in the next section
|
W07-0721 |
direc - tions ) . It is shown that
|
graph pruning
|
guarantees the efficiency of
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S14-2034 |
pruning and packing algorithms . 3.1
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Graph pruning
|
Our PRUNING algorithm removes
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D14-1034 |
where I stands for a preposition .
|
Graph Pruning
|
. The edge set of our model consists
|
W07-0721 |
efficiency : we analyze different
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graph pruning
|
and we show the very low increase
|
W05-0834 |
systems are phrase-based . + Their
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graph pruning
|
method is suboptimal as it considers
|
J13-3007 |
neither domain heuristics nor the
|
graph pruning
|
could completely eliminate the
|
S15-2155 |
between individual node pairs and
|
graph pruning
|
or edge collapsing ( Kozareva
|
W07-0721 |
have experimented with different
|
graph pruning
|
showing that best translation
|
S10-1094 |
. 4 Knowledge-Based WSD using
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Graph Pruning
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Wordnet can be viewed as a graph
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D14-1088 |
described in Section 2.2.4 . Step 3 :
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Graph pruning
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( line 18 ) The hypernym graph
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J13-3007 |
regard to the two versions of our
|
graph pruning
|
algorithm , we found that TREE
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J13-3007 |
heuristic rules , we devised a novel
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graph pruning
|
algorithm , based on the Chu-Liu/Edmonds
|