PSG: a two-layer graph model for document summarization

doi:10.1007/s11704-013-2292-2

PSG: a two-layer graph model for document summarization

2013-11-15

7

PRE

AI

DOI：10.1007/s11704-013-2292-2

Original

Original request for help

Save

Abstract

En 中文

Graph model has been widely applied in document summarization by using sentence as the graph node, and the similarity between sentences as the edge. In this paper, a novel graph model for document summarization is presented, that not only sentences relevance but also phrases relevance information included in sentences are utilized. In a word, we construct a phrase-sentence two-layer graph structure model (PSG) to summarize document(s). We use this model for generic document summarization and query-focused summarization. The experimental results show that our model greatly outperforms existing work.

Keywords:

relationship graph

Markov random walk

document summarization

PSG: a two-layer graph model for document summarization

Abstract

Journal

Organization