Effectively Leveraging Entropy and Relevance for Summarization

Document summarization has attracted a lot of research interest since the 1960s. However, it still remains a challenging task on how to extract effective feature for automatic summarization. In this paper, we extract two features called entropy and relevance to leverage information from different perspectives for summarization. Experiments on unsupervised and supervised methods testify the effectiveness of leveraging the two features.

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