Single document Summarization based on Clustering Coefficient and Transitivity Analysis

Document summarization is a technique aimed to automatically extract the main ideas from electronic documents. With the fast increase of electronic documents available on the network, techniques for making efficient use of such documents become increasingly important. In this paper, we propose a novel algorithm, called TriangleSum for single document summarization based on graph theory. The algorithm builds a dependency graph for the document based on syntactic dependency relation analysis. The nodes represent words or phrases of high frequency, and edges represent dependency relations between them. Then, a modified version of clustering coefficient is used to measure the strength of connection between nodes in a graph. By identifying triangles of nodes, a part of the dependency graph can be extracted. At last, a set of key sentences that represent the main document information can be extracted. Keyword:summarization, dependency graph, clustering coefficient, transitivity analysis