W15-3041 and a feature produced with word embedding /embedding/NN models ( SHEF - QuEst + + ) .
W15-3124 sen - timental features , word embedding /embedding/NN is employed for acquiring expanded
W15-3814 literature . Recent advances in word embedding /embedding/NN make computation of word distribution
W15-3820 representations , also known as word embedding /embedding/NN , have been shown to improve
W15-3822 method called Surrounding based embedding /embed/VBG feature ( SBE ) , and two newly
W15-4005 regression to learn the bilingual word embedding /embedding/NN using compositional distributional
W15-4310 representation . Besides word embedding /embedding/NN , we use partof-speech ( POS
W96-0413 set for the same variable in the embedding /embedding/NN structure . An inner quantifier
W97-0901 reports on SRA 's experience in embedding /embedding/NN name recognition in these three
W98-1311 Another aspect to consider is the embedding /embedding/NN of the single elements of the
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