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PSG: a two-layer graph model for document summarization
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DOI：10.1007/s11704-013-2292-2.png)
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摘要
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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.
Keyword:
relationship graph
Markov random walk
document summarization
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4.6
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1.6K
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