Document update summarization using incremental hierarchical clustering

Dingding Wang, Tao Li
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引用次数: 76

Abstract

Document summarization has become a hot topic in recent years. However, most of existing summarization methods work on a batch of documents and do not consider that documents may arrive in a sequence and the corresponding summaries need to be updated in real time. In this paper, we propose a new summarization method based on an incremental hierarchical clustering framework to update summaries as soon as a new document arrives. Extensive experimental results demonstrate the effectiveness and efficiency of our proposed method.
使用增量分层聚类的文档更新摘要
文献摘要是近年来研究的热点。然而,现有的大多数摘要方法都是处理一批文档,没有考虑到文档可能是按顺序到达的,相应的摘要需要实时更新。在本文中,我们提出了一种新的基于增量层次聚类框架的摘要方法,以便在新文档到达时更新摘要。大量的实验结果证明了该方法的有效性和高效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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