Sentence Extraction by Graph Neural Networks

被引：0

作者：

Muratore, Donatella ^{[1
]}

Hagenbuchner, Markus ^{[2
]}

Scarselli, Franco ^{[1
]}

Tsoi, Ah Chung ^{[3
]}

机构：

[1] Univ Siena, Via Laterina 8, I-53100 Siena, Italy

[2] Univ Wollongong, Wollongong, NSW, Australia

[3] Univ Hong Kong, Hong Kong, Peoples R China

来源：

ARTIFICIAL NEURAL NETWORKS (ICANN 2010), PT III | 2010年 / 6354卷

基金：

澳大利亚研究理事会;

关键词：

Sentence Extraction; Text Summarization; Graph Neural Network; TextRank;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we will apply a recently proposed connectionist model, namely, the Graph Neural Network, for processing the graph formed by considering each sentence in a document as a node and the relationship between two sentences as an edge. Using commonly accepted evaluation protocols, the ROGUE toolkit, the technique was applied to two text summarization benchmarks, namely DUC-2001 and DUC-2002 respectively. It is found that the results obtained are comparable to the best results achieved using other techniques.

引用

页码：237 / +

页数：2

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