{"id":151946,"date":"2006-04-01T00:00:00","date_gmt":"2006-04-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/summarizing-answers-for-complicated-questions\/"},"modified":"2018-10-16T19:57:15","modified_gmt":"2018-10-17T02:57:15","slug":"summarizing-answers-for-complicated-questions","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/summarizing-answers-for-complicated-questions\/","title":{"rendered":"Summarizing Answers for Complicated Questions"},"content":{"rendered":"

This paper describes the multi-document summarization system designed by the Webclopedia team from ISI for DUC 2005. In contrast to the past DUCs and previous designs, this version of our summarizer consists of a query-interpretation component that directly analyzes the given user profile and topic narrative for each document cluster before creating a corresponding summary. This system ranks 4th on ROUGE-1, 7th on ROUGE-2 and ROUGESU4. Evaluations conducted by Basis Elements show this system ranks 6th among 32 automatic systems.<\/p>\n","protected":false},"excerpt":{"rendered":"

This paper describes the multi-document summarization system designed by the Webclopedia team from ISI for DUC 2005. In contrast to the past DUCs and previous designs, this version of our summarizer consists of a query-interpretation component that directly analyzes the given user profile and topic narrative for each document cluster before creating a corresponding summary. 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