Affinity-Preserving Random Walk for Multi-Document Summarization
نویسندگان
چکیده
Multi-document summarization provides users with a short text that summarizes the information in a set of related documents. This paper introduces affinitypreserving random walk to the summarization task, which preserves the affinity relations of sentences by an absorbing random walk model. Meanwhile, we put forward adjustable affinity-preserving random walk to enforce the diversity constraint of summarization in the random walk process. The ROUGE evaluations on DUC 2003 topic-focused summarization task and DUC 2004 generic summarization task show the good performance of our method, which has the best ROUGE2 recall among the graph-based ranking methods.
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