Autoencoder for polysemous word

Authors:
Cheng-Yuan Liou;Chen-Wei Cheng;Jiun-Wei Liou;Daw-Ran Liou
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, Republic of China;Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, Republic of China,Institute of Statistical Science, Academia Sinica, Taiwan, Republic of China;Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, Republic of China;Sibley School of Mechanical and Aerospace Engineering, Cornell University
Venue:
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Year:
2012

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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.