Distributed representation of word by using Elman network. (1st January 2013) - Liou, Jiun-Wei; Cheng, Wei-Chen; Huang, Jau-Chi; Liou, Cheng-Yuan
This paper presents a novel training method for Elman network to encode the words in literary works. This network has been used in studying limited simple artificial sentences with varying degrees of success. This paper shows how to use it to process real-world works. Both word codes and network weights can be accomplished by the method. Each trained code is a distributed representation of its word. The training error can be drastically reduced by iteratively re-encoding the representations. Several distinct findings and results during the training process are reported.