W07-0710 |
all subsequent experiments of
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feature expansion
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. 4.3 BLEU Training Results We
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P14-2043 |
using a relatively straightforward
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feature expansion
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scheme . Experiments on five
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P13-1129 |
alternation pattern by utilizing a
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feature expansion
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scheme . For each utterance n
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P11-1014 |
the effect of not performing any
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feature expansion
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. We simply train a binary classifier
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P11-1014 |
sentiment sensitive thesaurus for
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feature expansion
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. Given a labeled or an unlabeled
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P11-1014 |
Shen et al. , 2009 ) . However ,
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feature expansion
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techniques have not previously
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P14-1130 |
tensor represents a substantial
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feature expansion
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. The arc score stensor ( h --
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P11-1014 |
sentiment sensitive thesaurus for
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feature expansion
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is useful for cross-domain sentiment
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D15-1049 |
preceding paragraph : an intuitive
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representation of the domain
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W07-0710 |
have introduced a non-parametric
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feature expansion
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, which guarantees invariance
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W13-2250 |
At the end , when all possible
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feature expansions
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are considered , each example
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P11-1014 |
reviews . 4 Feature Expansion Our
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feature expansion
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phase augments a feature vector
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P11-1014 |
from a large set of reviews . 4
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Feature Expansion
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Our feature expansion phase augments
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P07-2017 |
the testing speed of different
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feature expansion
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techniques , namely , array visiting
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W14-3411 |
using a generic solution such as
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feature expansion
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based on distributional similarity
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W06-1208 |
, and were most effective as a
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feature expansion
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algorithm . The only obvious
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P07-2017 |
provide a more efficient solution to
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feature expansion
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when d is set more than two .
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P06-2087 |
analysis , we propose to base our
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feature expansion
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also on argumentative cri - teria
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P14-1130 |
counters the otherwise uncontrolled
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feature expansion
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. More - over , by controlling
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P03-1004 |
polynomial kernel allows such
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feature expansion
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without loss of generality or
|