In this paper, we will apply a recently proposed connectionist model, namely, the Graph Neural Network, for processing the graph formed by considering each sentence in a document as a node and the relationship between two sentences as an edge. Using commonly accepted evaluation protocols, the ROGUE toolkit, the technique was applied to two text summarization benchmarks, namely DUC-2001 and DUC-2002 respectively. It is found that the results obtained are comparable to the best results achieved using other techniques. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Muratore, D., Hagenbuchner, M., Scarselli, F., & Tsoi, A. C. (2010). Sentence extraction by graph neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6354 LNCS, pp. 237–246). https://doi.org/10.1007/978-3-642-15825-4_29
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