Analysis of Sentence Ordering Based on Support Vector Machine

被引：1

作者：

Peng, Gongfu ^{[1
]}

He, Yanxiang ^{[1
]}

Tian, Ye ^{[1
]}

Tian, Yingsheng ^{[1
]}

Wen, Weidong ^{[1
]}

机构：

[1] Wuhan Univ, Comp Sch, Wuhan 430079, Peoples R China

来源：

2009 PACIFIC-ASIA CONFERENCE ON KNOWLEDGE ENGINEERING AND SOFTWARE ENGINEERING, PROCEEDINGS | 2009年

关键词：

Sentence ordering; SVM;

D O I：

10.1109/KESE.2009.14

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 present a practical method of sentence ordering in multi-document summarization tasks of Chinese language. By using Support Vector Machine (SVM), we classify the sentences of a summary into several groups in rough position according to the source documents. Then we adjust the sentence sequence of each group according to the estimation of directional relativity of adjacent sentences, and find the sequence of each group. Finally, we connect the sequences of different groups to generate the final order of the summary. Experimental results indicate that this method works better than most existing methods of sentence ordering.

引用

页码：25 / 27

页数：3

共 11 条

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