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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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> .
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