other,21-1-N04-1024,bq |
discourse elements
</term>
( e.g. ,
<term>
|
thesis statements
|
</term>
) . We describe a new system that
|
#6666
CriterionSM Online Essay Evaluation Service includes a capability that labels sentences in student writing with essay-based discourse elements (e.g.,thesis statements). |
other,8-3-N04-1024,bq |
</term>
of
<term>
sentences
</term>
based on
<term>
|
semantic similarity measures
|
</term>
and
<term>
discourse structure
</term>
|
#6698
This system identifies features of sentences based onsemantic similarity measures and discourse structure. |
other,12-3-N04-1024,bq |
semantic similarity measures
</term>
and
<term>
|
discourse structure
|
</term>
. A
<term>
support vector machine
</term>
|
#6702
This system identifies features of sentences based on semantic similarity measures anddiscourse structure. |
other,17-4-N04-1024,bq |
coherence
</term>
due to relatedness to the
<term>
|
essay question
|
</term>
and relatedness between
<term>
discourse
|
#6722
A support vector machine uses these features to capture breakdowns in coherence due to relatedness to theessay question and relatedness between discourse elements. |
other,9-4-N04-1024,bq |
these
<term>
features
</term>
to capture
<term>
|
breakdowns in coherence
|
</term>
due to relatedness to the
<term>
essay
|
#6714
A support vector machine uses these features to capturebreakdowns in coherence due to relatedness to the essay question and relatedness between discourse elements. |
other,22-4-N04-1024,bq |
question
</term>
and relatedness between
<term>
|
discourse elements
|
</term>
.
<term>
Intra-sentential quality
</term>
|
#6727
A support vector machine uses these features to capture breakdowns in coherence due to relatedness to the essay question and relatedness betweendiscourse elements. |
other,0-5-N04-1024,bq |
between
<term>
discourse elements
</term>
.
<term>
|
Intra-sentential quality
|
</term>
is evaluated with
<term>
rule-based
|
#6730
A support vector machine uses these features to capture breakdowns in coherence due to relatedness to the essay question and relatedness between discourse elements.Intra-sentential quality is evaluated with rule-based heuristics. |
other,10-1-N04-1024,bq |
</term>
includes a capability that labels
<term>
|
sentences
|
</term>
in student
<term>
writing
</term>
with
|
#6655
CriterionSM Online Essay Evaluation Service includes a capability that labelssentences in student writing with essay-based discourse elements (e.g., thesis statements). |
other,16-2-N04-1024,bq |
by evaluating multiple aspects of
<term>
|
coherence
|
</term>
in
<term>
essays
</term>
. This system
|
#6686
We describe a new system that enhances Criterion's capability, by evaluating multiple aspects ofcoherence in essays. |
other,5-3-N04-1024,bq |
identifies
<term>
features
</term>
of
<term>
|
sentences
|
</term>
based on
<term>
semantic similarity
|
#6695
This system identifies features ofsentences based on semantic similarity measures and discourse structure. |
other,15-1-N04-1024,bq |
in student
<term>
writing
</term>
with
<term>
|
essay-based discourse elements
|
</term>
( e.g. ,
<term>
thesis statements
</term>
|
#6660
CriterionSM Online Essay Evaluation Service includes a capability that labels sentences in student writing withessay-based discourse elements (e.g., thesis statements). |
other,18-2-N04-1024,bq |
aspects of
<term>
coherence
</term>
in
<term>
|
essays
|
</term>
. This system identifies
<term>
features
|
#6688
We describe a new system that enhances Criterion's capability, by evaluating multiple aspects of coherence inessays. |
other,10-6-N04-1024,bq |
system yields higher performance than a
<term>
|
baseline
|
</term>
on all three aspects .
<term>
Information
|
#6748
Results indicate that the system yields higher performance than abaseline on all three aspects. |
other,13-1-N04-1024,bq |
labels
<term>
sentences
</term>
in student
<term>
|
writing
|
</term>
with
<term>
essay-based discourse elements
|
#6658
CriterionSM Online Essay Evaluation Service includes a capability that labels sentences in studentwriting with essay-based discourse elements (e.g., thesis statements). |
tool,0-1-N04-1024,bq |
specific
<term>
loss functions
</term>
.
<term>
|
CriterionSM Online Essay Evaluation Service
|
</term>
includes a capability that labels
|
#6645
Our results show that MBR decoding can be used to tune statistical MT performance for specific loss functions.CriterionSM Online Essay Evaluation Service includes a capability that labels sentences in student writing with essay-based discourse elements (e.g., thesis statements). |
tech,1-4-N04-1024,bq |
<term>
discourse structure
</term>
. A
<term>
|
support vector machine
|
</term>
uses these
<term>
features
</term>
to
|
#6706
Asupport vector machine uses these features to capture breakdowns in coherence due to relatedness to the essay question and relatedness between discourse elements. |
tool,7-2-N04-1024,bq |
describe a new system that enhances
<term>
|
Criterion
|
</term>
's capability , by evaluating multiple
|
#6677
We describe a new system that enhancesCriterion's capability, by evaluating multiple aspects of coherence in essays. |
tech,5-5-N04-1024,bq |
Intra-sentential quality
</term>
is evaluated with
<term>
|
rule-based heuristics
|
</term>
. Results indicate that the system
|
#6735
Intra-sentential quality is evaluated withrule-based heuristics. |
other,6-4-N04-1024,bq |
support vector machine
</term>
uses these
<term>
|
features
|
</term>
to capture
<term>
breakdowns in coherence
|
#6711
A support vector machine uses thesefeatures to capture breakdowns in coherence due to relatedness to the essay question and relatedness between discourse elements. |
other,3-3-N04-1024,bq |
essays
</term>
. This system identifies
<term>
|
features
|
</term>
of
<term>
sentences
</term>
based on
<term>
|
#6693
This system identifiesfeatures of sentences based on semantic similarity measures and discourse structure. |