Summarizing Documents by Measuring the Importance of a Subset of Vertices within a Graph.
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.
Dept. Computer Science and Technology, Beijing 10084, China,  chenshouyuan@gmail.com.
Shouyuan
S
Chen
Minlie
M
Huang
Zhiyong
Z
Lu