PSG： a two-layer graph model for document summarization  

作　　者：Heng CHEN Hai JIN Feng ZHAO 

机构地区：[1]Service Computing Technology and System Lab & Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China

出　　处：《Frontiers of Computer Science》2014年第1期119-130,共12页中国计算机科学前沿（英文版）

摘　　要：Graph model has been widely applied in docu- ment summarization by using sentence as the graph node, and the similarity between sentences as the edge. In this paper, a novel graph model for document summarization is presented, that not only sentences relevance but also phrases relevance information included in sentences are utilized. In a word, we construct a phrase-sentence two-layer graph structure model （PSG） to summarize document（s） . We use this model for generic document summarization and query-focused sum- marization. The experimental results show that our model greatly outperforms existing work.Graph model has been widely applied in docu- ment summarization by using sentence as the graph node, and the similarity between sentences as the edge. In this paper, a novel graph model for document summarization is presented, that not only sentences relevance but also phrases relevance information included in sentences are utilized. In a word, we construct a phrase-sentence two-layer graph structure model （PSG） to summarize document（s） . We use this model for generic document summarization and query-focused sum- marization. The experimental results show that our model greatly outperforms existing work.

关 键 词：relationship graph Markov random walk doc-ument summarization 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] G356.7[自动化与计算机技术—计算机科学与技术]