other,7-1-H05-1005,ak In this paper , we use the <term> information redundancy </term> in multilingual input to correct <term> errors </term> in <term> machine translation </term> and thus improve the quality of multilingual summaries .
tech,16-1-H05-1005,ak In this paper , we use the <term> information redundancy </term> in multilingual input to correct <term> errors </term> in <term> machine translation </term> and thus improve the quality of multilingual summaries .
tech,5-2-H05-1005,ak We consider the case of <term> multi-document summarization </term> , where the input documents are in Arabic , and the output summary is in English .
other,13-3-H05-1005,ak Typically , information that makes it to a summary appears in many different <term> lexical-syntactic forms </term> in the input documents .
tech,6-4-H05-1005,ak Further , the use of multiple <term> machine translation systems </term> provides yet more <term> redundancy </term> , yielding different ways to realize that information in English .
other,12-4-H05-1005,ak Further , the use of multiple <term> machine translation systems </term> provides yet more <term> redundancy </term> , yielding different ways to realize that information in English .
other,6-5-H05-1005,ak We demonstrate how <term> errors </term> in the <term> machine translations </term> of the input Arabic documents can be corrected by identifying and generating from such <term> redundancy </term> , focusing on <term> noun phrases </term> .
other,22-5-H05-1005,ak We demonstrate how <term> errors </term> in the <term> machine translations </term> of the input Arabic documents can be corrected by identifying and generating from such <term> redundancy </term> , focusing on <term> noun phrases </term> .
other,26-5-H05-1005,ak We demonstrate how <term> errors </term> in the <term> machine translations </term> of the input Arabic documents can be corrected by identifying and generating from such <term> redundancy </term> , focusing on <term> noun phrases </term> .
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