Abstract
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.
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Muratore, D., Hagenbuchner, M., Scarselli, F., Tsoi, A.C. (2010). Sentence Extraction by Graph Neural Networks. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15825-4_29
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DOI: https://doi.org/10.1007/978-3-642-15825-4_29
Publisher Name: Springer, Berlin, Heidelberg
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