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Do Summaries Help? A Task-Based Evaluation of Multi-Document Summarization

Hirschberg, Julia Bell; McKeown, Kathleen; Passonneau, Rebecca; Elson, David K.; Nenkova, Ani

We describe a task-based evaluation to determine whether multi-document summaries measurably improve user performance when using online news browsing systems for directed research. We evaluated the multi-document summaries generated by Newsblaster, a robust news browsing system that clusters online news articles and summarizes multiple articles on each event. Four groups of subjects were asked to perform the same time-restricted fact-gathering tasks, reading news under different conditions: no summaries at all, single sentence summaries drawn from one of the articles, Newsblaster multi-document summaries, and human summaries. Our results show that, in comparison to source documents only, the quality of reports assembled using Newsblaster summaries was significantly better and user satisfaction was higher with both Newsblaster and human summaries.

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More About This Work

Academic Units
Computer Science
Publisher
Proceedings of ICASSP, Special Session on Human Language Technology Applications and Challenges for Speech Processing, 2005
Published Here
June 12, 2013
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