Abstract
In this paper, we present a novel approach for automatic summarization. We believe redundancy is the most important factor in building a summary automatically. We want to detect it automatically with an unsupervized method that could apply to any multi-document summarization task. CBSEAS, the system implementing our approach integrates a new method to detect redundancy at its very core, in order to produce more expressive summaries than previous approaches. However, the evaluation of our system at TAC 2008 –Text Analysis Conference– revealed some failings. We propose to make up for these weaknesses by using document structure inside the automatic summarizer.
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