Multi-document summarization based on unsupervised clustering

被引：0

作者：

Ji, Paul ^{[1
]}

机构：

[1] Univ Oxford, Ctr Linguist & Philol, Oxford, England

来源：

INFORMATION RETRIEVAL TECHNOLOLGY, PROCEEDINGS | 2006年 / 4182卷

关键词：

multi-document summarization; clustering; entropy; optimization;

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 propose a method for multi-document summarization based on unsupervised clustering. First, the main topics are determined by a MDL-based clustering strategy capable of inferring optimal cluster numbers. Then, the problem of multi-document summarization is formalized on the clusters using an entropy-based object function.

引用

页码：560 / 566

页数：7