Identifying similarities and differences across English and Arabic news

We present a new approach for summarizing topically clustered documents from two sources, En-glish and machine translated Arabic texts, that presents users with an overview of the differences in content of the two sources, and information that is supported by both sources. Our approach to multilingual multi-document summa-rization clusters all input document sentences, and identifies sentence clusters that contain information exclusive to the Arabic documents, information exclusive to the English documents, and information that is similar between the two. The result is a three-part summary describing information about the event that comes exclusively from Arabic sources, information coming exclusively from English sources, and information that both sources consider important, enabling analysts to more quickly understand differences between incoming documents from different sources. We report on a user evaluation of the summaries.