The Algorithm of Automatic Text Summarization Based on Network Representation Learning

摘要：

　　The graph models are an important method in automatic text summarization.However,there will be problems of vector sparseness and information redundancy in text map to graph.In this paper,we propose a graph clustering summarization algorithm based on network representation learning.The sentences graph was construed by TF-IDF,and controlled the number of edges by a threshold.The Node2Vec is used to embedding the graph,and the sentences were clustered by k-means.Finally,the Modularity is used to control the number of clusters,and generating a brief summary of the document.The experiments on the MultiLing 2013 show the proposed algorithm improves the F-Score in ROUGE-1 and ROUGE-2.

关键词： Text summarization Network representation learning Graph clustering Modularity

作者: Xinghao Song Chunming Yang Hui Zhang Xujian Zhao

作者单位: School of Computer Science and Technology,Southwest University of Science and Technology,Mianyang 62 School of Computer Science and Technology,Southwest University of Science and Technology,Mianyang 62 School of Science,Southwest University of Science and Technology,Mianyang 621020,Sichuan,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 362-371

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）