Abstract
We present a novel method to train the Elman network to learn literal works. This paper reports findings and results during the training process. Both codes and network weights are trained by using this method. The training error can be greatly reduced by iteratively re-encoding all words. © 2011 Springer Berlin Heidelberg.
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APA
Huang, J. C., Cheng, W. C., & Liou, C. Y. (2011). Distributed representation of word. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6591 LNAI, pp. 169–176). Springer Verlag. https://doi.org/10.1007/978-3-642-20039-7_17
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