other,8-3-H05-1005,bq |
Typically , information that makes it to a
<term>
summary
</term>
appears in many different
<term>
lexical-syntactic forms
</term>
in the input
<term>
documents
</term>
.
|
#7184
Typically, information that makes it to asummary appears in many different lexical-syntactic forms in the input documents. |
other,13-3-H05-1005,bq |
Typically , information that makes it to a
<term>
summary
</term>
appears in many different
<term>
lexical-syntactic forms
</term>
in the input
<term>
documents
</term>
.
|
#7189
Typically, information that makes it to a summary appears in many differentlexical-syntactic forms in the input documents. |
other,14-2-H05-1005,bq |
We consider the case of
<term>
multi-document summarization
</term>
, where the input
<term>
documents
</term>
are in
<term>
Arabic
</term>
, and the output
<term>
summary
</term>
is in
<term>
English
</term>
.
|
#7166
We consider the case of multi-document summarization, where the input documents are inArabic, and the output summary is in English. |
other,16-1-H05-1005,bq |
In this paper , we use the
<term>
information redundancy
</term>
in
<term>
multilingual input
</term>
to correct errors in
<term>
machine translation
</term>
and thus improve the quality of
<term>
multilingual summaries
</term>
.
|
#7141
In this paper, we use the information redundancy in multilingual input to correct errors inmachine translation and thus improve the quality of multilingual summaries. |
other,22-4-H05-1005,bq |
Further , the use of multiple
<term>
machine translation systems
</term>
provides yet more
<term>
redundancy
</term>
, yielding different ways to realize that
<term>
information
</term>
in
<term>
English
</term>
.
|
#7218
Further, the use of multiple machine translation systems provides yet more redundancy, yielding different ways to realize that information inEnglish. |
other,22-2-H05-1005,bq |
We consider the case of
<term>
multi-document summarization
</term>
, where the input
<term>
documents
</term>
are in
<term>
Arabic
</term>
, and the output
<term>
summary
</term>
is in
<term>
English
</term>
.
|
#7174
We consider the case of multi-document summarization, where the input documents are in Arabic, and the output summary is inEnglish. |
other,10-1-H05-1005,bq |
In this paper , we use the
<term>
information redundancy
</term>
in
<term>
multilingual input
</term>
to correct errors in
<term>
machine translation
</term>
and thus improve the quality of
<term>
multilingual summaries
</term>
.
|
#7135
In this paper, we use the information redundancy inmultilingual input to correct errors in machine translation and thus improve the quality of multilingual summaries. |
other,18-3-H05-1005,bq |
Typically , information that makes it to a
<term>
summary
</term>
appears in many different
<term>
lexical-syntactic forms
</term>
in the input
<term>
documents
</term>
.
|
#7194
Typically, information that makes it to a summary appears in many different lexical-syntactic forms in the inputdocuments. |
other,11-5-H05-1005,bq |
We demonstrate how errors in the
<term>
machine translations
</term>
of the input
<term>
Arabic documents
</term>
can be corrected by identifying and generating from such
<term>
redundancy
</term>
, focusing on
<term>
noun phrases
</term>
.
|
#7231
We demonstrate how errors in the machine translations of the inputArabic documents can be corrected by identifying and generating from such redundancy, focusing on noun phrases. |
other,11-2-H05-1005,bq |
We consider the case of
<term>
multi-document summarization
</term>
, where the input
<term>
documents
</term>
are in
<term>
Arabic
</term>
, and the output
<term>
summary
</term>
is in
<term>
English
</term>
.
|
#7163
We consider the case of multi-document summarization, where the inputdocuments are in Arabic, and the output summary is in English. |
other,12-4-H05-1005,bq |
Further , the use of multiple
<term>
machine translation systems
</term>
provides yet more
<term>
redundancy
</term>
, yielding different ways to realize that
<term>
information
</term>
in
<term>
English
</term>
.
|
#7208
Further, the use of multiple machine translation systems provides yet moreredundancy, yielding different ways to realize that information in English. |
tech,6-4-H05-1005,bq |
Further , the use of multiple
<term>
machine translation systems
</term>
provides yet more
<term>
redundancy
</term>
, yielding different ways to realize that
<term>
information
</term>
in
<term>
English
</term>
.
|
#7202
Further, the use of multiplemachine translation systems provides yet more redundancy, yielding different ways to realize that information in English. |
tech,5-2-H05-1005,bq |
We consider the case of
<term>
multi-document summarization
</term>
, where the input
<term>
documents
</term>
are in
<term>
Arabic
</term>
, and the output
<term>
summary
</term>
is in
<term>
English
</term>
.
|
#7157
We consider the case ofmulti-document summarization, where the input documents are in Arabic, and the output summary is in English. |
other,24-1-H05-1005,bq |
In this paper , we use the
<term>
information redundancy
</term>
in
<term>
multilingual input
</term>
to correct errors in
<term>
machine translation
</term>
and thus improve the quality of
<term>
multilingual summaries
</term>
.
|
#7149
In this paper, we use the information redundancy in multilingual input to correct errors in machine translation and thus improve the quality ofmultilingual summaries. |
other,26-5-H05-1005,bq |
We demonstrate how errors in the
<term>
machine translations
</term>
of the input
<term>
Arabic documents
</term>
can be corrected by identifying and generating from such
<term>
redundancy
</term>
, focusing on
<term>
noun phrases
</term>
.
|
#7246
We demonstrate how errors in the machine translations of the input Arabic documents can be corrected by identifying and generating from such redundancy, focusing onnoun phrases. |
other,19-2-H05-1005,bq |
We consider the case of
<term>
multi-document summarization
</term>
, where the input
<term>
documents
</term>
are in
<term>
Arabic
</term>
, and the output
<term>
summary
</term>
is in
<term>
English
</term>
.
|
#7171
We consider the case of multi-document summarization, where the input documents are in Arabic, and the outputsummary is in English. |
other,22-5-H05-1005,bq |
We demonstrate how errors in the
<term>
machine translations
</term>
of the input
<term>
Arabic documents
</term>
can be corrected by identifying and generating from such
<term>
redundancy
</term>
, focusing on
<term>
noun phrases
</term>
.
|
#7242
We demonstrate how errors in the machine translations of the input Arabic documents can be corrected by identifying and generating from suchredundancy, focusing on noun phrases. |
other,20-4-H05-1005,bq |
Further , the use of multiple
<term>
machine translation systems
</term>
provides yet more
<term>
redundancy
</term>
, yielding different ways to realize that
<term>
information
</term>
in
<term>
English
</term>
.
|
#7216
Further, the use of multiple machine translation systems provides yet more redundancy, yielding different ways to realize thatinformation in English. |
other,6-5-H05-1005,bq |
We demonstrate how errors in the
<term>
machine translations
</term>
of the input
<term>
Arabic documents
</term>
can be corrected by identifying and generating from such
<term>
redundancy
</term>
, focusing on
<term>
noun phrases
</term>
.
|
#7226
We demonstrate how errors in themachine translations of the input Arabic documents can be corrected by identifying and generating from such redundancy, focusing on noun phrases. |
other,7-1-H05-1005,bq |
In this paper , we use the
<term>
information redundancy
</term>
in
<term>
multilingual input
</term>
to correct errors in
<term>
machine translation
</term>
and thus improve the quality of
<term>
multilingual summaries
</term>
.
|
#7132
In this paper, we use theinformation redundancy in multilingual input to correct errors in machine translation and thus improve the quality of multilingual summaries. |