Key Sentence Extraction from Single Document based on Triangle Analysis in Dependency Graph

Document summarization is a technique aimed to automatically extract main ideas from electronic documents. In this paper, we propose a novel algorithm, called TriangleSum for key sentence extraction from single document based on graph theory. The algorithm builds a dependency graph for the underlying document based on co-occurrence relation as well as syntactic dependency relations. The nodes represent words or phrases of high frequency, and edges represent dependency, or co-occurrence relations between them. The clustering coefficient is computed from each node to measure the strength of connection between the node and its neighborhood nodes in a graph. By identifying triangles of nodes in the graph, a part of the dependency graph can be extracted as marks of key sentences. At last, a set of key sentences that represent the main document information can be extracted. Keywords— document summarization; key sentence; dependency structure analysis; clustering coefficient; triangle finding