C90-3072 |
method has been developed for easy
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word classification
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. 1 . Introduction After some
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C04-1115 |
in application to the task of
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word classification
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. The structure of the paper
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C00-1002 |
acquisition model and tested it ; on a
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word classification
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task . The main points of our
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D09-1084 |
strings . They evaluate NGD in a
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word classification
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task . Unfortunately NGD only
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C94-2198 |
fimction to evaluate the quality of
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word classification
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. The Metropolis algorithm specifies
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D13-1084 |
the following metrics : •
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Word classification
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precision ( P ) , recall ( R
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E12-1065 |
sets are used in previous work in
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word classification
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, such as ( Lin and Pantel ,
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D14-1151 |
development and test sets . For all
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word classification
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, coreference-based features
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C04-1200 |
Word Sentiment Classifier 2.1.1
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Word Classification
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Models For word sentiment classification
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E97-1033 |
constrains the task of building the
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word classification
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trees since the major distinctions
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C04-1115 |
supervised . In the context of
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word classification
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this procedure can be formalized
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C92-2085 |
suhlanguages requires different
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word classification
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schemes . We have to construct
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C86-1060 |
lt is called The process of the
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word classification
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based on the pattern of relations
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C04-1115 |
representations on tasks including
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word classification
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( e.g. , Ciaramita 2002 ) . The
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C65-1022 |
" walk " as its member . This
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word classification
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has not been tried yet on the
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D13-1062 |
mapping between their heterogeneous
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word classification
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, and the mapping between heterogeneous
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E97-1033 |
the POS tags ; thus we build a
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word classification
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tree for each POS tag . This
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E03-1084 |
help in this research . <title>
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Word classification
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based on combined measures of
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A92-1013 |
parsing is used for the purpose of
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word classification
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. All these studies are based
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D14-1151 |
experiments in two modes : all
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word classification
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( all pairs are considered )
|