D11-1014 |
can be used to efficiently learn
|
feature encodings
|
which are useful for classification
|
D08-1084 |
features . We begin with boolean
|
features encoding
|
the type of each edit . We expect
|
D15-1016 |
can be used to efficiently learn
|
feature encodings
|
that are useful for classification
|
H05-1045 |
structure , which our rather simple
|
feature encoding
|
for CRF could not capture well
|
H05-1045 |
to act as an opinion word for
|
feature encoding
|
. After syntactic chunking and
|
E12-1072 |
constructions . 11 A : a binary
|
feature encoding
|
the presence or absence of the
|
D08-1006 |
constant and the { fi } 's are
|
features encoding
|
some information about the sentence
|
J11-4006 |
novel features . Firstly , we add
|
features encoding
|
the non-head words when the window
|
E06-1038 |
3.3 Learning Having defined a
|
feature encoding
|
and decoding algorithm , the
|
E14-1012 |
higher prediction accuracy . Simple
|
feature encodings
|
such as unigrams are frequently
|
E14-1012 |
strategic combination of rich
|
feature encodings
|
and structured modeling approach
|
D10-1039 |
from the parse tree , as well as
|
features encoding
|
the lexico-syntactic context
|
D08-1069 |
, these findings suggest that
|
features encoding
|
some aspect of salience ( e.g.
|
J96-3001 |
values . A typical case might be a
|
feature encoding
|
the identifier of a particular
|
D08-1032 |
the sentence . 3.5.2 Syntactic
|
Feature Encoding
|
syntactic structure is easier
|
H05-1040 |
" informer spans , and various
|
feature encodings
|
. Observe in Table 2 that the
|
D09-1123 |
words . • Part-of-Speech
|
Features encoding
|
source and target POS tags as
|
D11-1046 |
largely modeled alignments based on
|
features encoding
|
target-side English syntactic
|
D11-1113 |
discriminative linear ranking models with
|
features encoding
|
syntactic context , and we tested
|
D09-1123 |
, • Source Morphological
|
Features encoding
|
morphological and segmentation
|