Abstract
Instead of training a single code vector for a word by using Elman network [1], this work presents a method to train multi-code for the polysemous word where each code represents a different meaning of the word. These multiple codes can accommodate different meanings of a word and facilitate the operation of word-sense disambiguation in semantic space.
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Liou, CY., Cheng, CW., Liou, JW., Liou, DR. (2013). Autoencoder for Polysemous Word. In: Yang, J., Fang, F., Sun, C. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2012. Lecture Notes in Computer Science, vol 7751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36669-7_56
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DOI: https://doi.org/10.1007/978-3-642-36669-7_56
Publisher Name: Springer, Berlin, Heidelberg
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