哈尔滨工业大学学报（英文版）2005，Vol.12Issue(1)：91-94,4.
Research on multi-document summarization based on latent semantic indexing
Research on multi-document summarization based on latent semantic indexing
摘要
Abstract
A multi-document summarization method based on Latent Semantic Indexing (LSI) is proposed. The method combines several reports on the same issue into a matrix of terms and sentences, and uses a Singular Value Decomposition (SVD) to reduce the dimension of the matrix and extract features, and then the sentence similarity is computed. The sentences are clustered according to similarity of sentences. The centroid sentences are selected from each class. Finally, the selected sentences are ordered to generate the summarization. The evaluation and results are presented, which prove that the proposed methods are efficient.关键词
multi-document summarization/LSI (latent semantic indexing)/clusteringKey words
multi-document summarization/LSI (latent semantic indexing)/clustering分类
信息技术与安全科学引用本文复制引用
QIN Bing,LIU Ting,ZHANG Yu,LI Sheng..Research on multi-document summarization based on latent semantic indexing[J].哈尔滨工业大学学报（英文版）,2005,12(1):91-94,4.基金项目
Sponsored by the National Natural Science Foundation of China (Grant No. 60203020). （Grant No. 60203020）
