Document Mining using Graph Neural Network
Springer Berlin Heidelberg ; DEU, 2006
Online
Konferenz
Zugriff:
The Graph Neural Network is a relatively new machine learning method capable of encoding data as well as relationships between data elements. This paper applies the Graph Neural Network for the first time to a given learning task at an international competition on the classification of semi-structured documents. Within this setting, the Graph Neural Network is trained to encode and process a relatively large set of XML formatted documents. It will be shown that the performance using the Graph Neural Network approach significantly outperforms the results submitted by the best competitor.
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Document Mining using Graph Neural Network
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Autor/in / Beteiligte Person: | S. L., YONG ; M., HAGENBUCHNER ; A. C., TSOI ; SCARSELLI, FRANCO ; GORI, MARCO ; Norbert Fuhr, Mounia Lalmas, Andrew Trotman ; S. L., Yong ; M., Hagenbuchner ; A. C., Tsoi ; Scarselli, Franco ; Gori, Marco |
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Veröffentlichung: | Springer Berlin Heidelberg ; DEU, 2006 |
Medientyp: | Konferenz |
DOI: | 10.1007/978-3-540-73888-6_43 |
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