This paper presents a novel method of generating extractive summaries for multiple documents. Given a cluster of documents, we firstly construct a graph where each vertex represents a sentence and edges are created according to the asymmetric relationship between sentences. Then we develop a method to measure the importance of a subset of vertices by adding a super-vertex into the original graph. The importance of such a super-vertex is quantified as super-centrality, a quantitative measure for the importance of a subset of vertices within the whole graph. Finally, we propose a heuristic algorithm to find the best summary. Our method is evaluated with extensive experiments. The comparative results show that the proposed method outperforms other methods on several datasets.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3019581 | PMC |
| http://dx.doi.org/10.1109/WI-IAT.2009.46 | DOI Listing |
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