lr,18-4-P06-2001,bq |
using a bigger and a more homogeneous
<term>
|
corpus
|
</term>
to train , that is , a bigger
<term>
|
#11300
Finally, we have shown that these results can be improved using a bigger and a more homogeneouscorpus to train, that is, a bigger corpus written by one unique author. |
lr,27-4-P06-2001,bq |
</term>
to train , that is , a bigger
<term>
|
corpus
|
</term>
written by one unique
<term>
author
|
#11309
Finally, we have shown that these results can be improved using a bigger and a more homogeneous corpus to train, that is, a biggercorpus written by one unique author. |
lr,9-2-P06-2001,bq |
experiments , and trained with a little
<term>
|
corpus
|
</term>
of 100,000
<term>
words
</term>
, the
|
#11236
After several experiments, and trained with a littlecorpus of 100,000 words, the system guesses correctly not placing commas with a precision of 96% and a recall of 98%. |
measure(ment),10-3-P06-2001,bq |
<term>
precision
</term>
of 70 % and a
<term>
|
recall
|
</term>
of 49 % in the task of placing
<term>
|
#11271
It also gets a precision of 70% and arecall of 49% in the task of placing commas. |
measure(ment),23-2-P06-2001,bq |
not placing
<term>
commas
</term>
with a
<term>
|
precision
|
</term>
of 96 % and a
<term>
recall
</term>
of
|
#11250
After several experiments, and trained with a little corpus of 100,000 words, the system guesses correctly not placing commas with aprecision of 96% and a recall of 98%. |
measure(ment),29-2-P06-2001,bq |
<term>
precision
</term>
of 96 % and a
<term>
|
recall
|
</term>
of 98 % . It also gets a
<term>
precision
|
#11256
After several experiments, and trained with a little corpus of 100,000 words, the system guesses correctly not placing commas with a precision of 96% and arecall of 98%. |
measure(ment),4-3-P06-2001,bq |
recall
</term>
of 98 % . It also gets a
<term>
|
precision
|
</term>
of 70 % and a
<term>
recall
</term>
of
|
#11265
It also gets aprecision of 70% and a recall of 49% in the task of placing commas. |
other,12-2-P06-2001,bq |
little
<term>
corpus
</term>
of 100,000
<term>
|
words
|
</term>
, the system guesses correctly not
|
#11239
After several experiments, and trained with a little corpus of 100,000words, the system guesses correctly not placing commas with a precision of 96% and a recall of 98%. |
other,19-3-P06-2001,bq |
</term>
of 49 % in the task of placing
<term>
|
commas
|
</term>
. Finally , we have shown that these
|
#11280
It also gets a precision of 70% and a recall of 49% in the task of placingcommas. |
other,20-2-P06-2001,bq |
system guesses correctly not placing
<term>
|
commas
|
</term>
with a
<term>
precision
</term>
of 96
|
#11247
After several experiments, and trained with a little corpus of 100,000 words, the system guesses correctly not placingcommas with a precision of 96% and a recall of 98%. |
other,25-1-P06-2001,bq |
in a
<term>
grammar checker
</term>
for
<term>
|
Basque
|
</term>
. After several experiments , and
|
#11225
In this paper, we describe the research using machine learning techniques to build a comma checker to be integrated in a grammar checker forBasque. |
other,32-4-P06-2001,bq |
corpus
</term>
written by one unique
<term>
|
author
|
</term>
. This paper presents an
<term>
unsupervised
|
#11314
Finally, we have shown that these results can be improved using a bigger and a more homogeneous corpus to train, that is, a bigger corpus written by one uniqueauthor. |
tech,15-1-P06-2001,bq |
learning techniques
</term>
to build a
<term>
|
comma checker
|
</term>
to be integrated in a
<term>
grammar
|
#11215
In this paper, we describe the research using machine learning techniques to build acomma checker to be integrated in a grammar checker for Basque. |
tech,22-1-P06-2001,bq |
checker
</term>
to be integrated in a
<term>
|
grammar checker
|
</term>
for
<term>
Basque
</term>
. After several
|
#11222
In this paper, we describe the research using machine learning techniques to build a comma checker to be integrated in agrammar checker for Basque. |
tech,9-1-P06-2001,bq |
paper , we describe the research using
<term>
|
machine learning techniques
|
</term>
to build a
<term>
comma checker
</term>
|
#11209
In this paper, we describe the research usingmachine learning techniques to build a comma checker to be integrated in a grammar checker for Basque. |