| Presentation | 2006-05-26 A model of word sequence prediction by using bigram Yoshihisa SHINOZAWA, Kengo UEHARA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Elman proposed simple recurrent network which is a model of language acquisition. Elman showed that SRN learns to predict the next word of the sentences and can acquire grammatical concepts and meanings. We think that it is difficult for SRN to learn the sentences which contain a number of words, especially to learn new words. We improve SRN and propose a model of word sequence prediction which learns new words additionally. We propose how to learn to predict the next words by distributed networks, whose structure is decided by using bigram. We evaluate our model with learning of next word prediction. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Simple Recurrent Network / Word acquisition / Word sequence prediction / Bigram |
| Paper # | NC2006-8 |
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| Committee | NC |
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| Conference Date | 2006/5/19(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A model of word sequence prediction by using bigram |
| Sub Title (in English) | |
| Keyword(1) | Simple Recurrent Network |
| Keyword(2) | Word acquisition |
| Keyword(3) | Word sequence prediction |
| Keyword(4) | Bigram |
| 1st Author's Name | Yoshihisa SHINOZAWA |
| 1st Author's Affiliation | Department of Administration Engineering, Faculty of Science and Technology, Keio University() |
| 2nd Author's Name | Kengo UEHARA |
| 2nd Author's Affiliation | Laboratory of Administration Engineering |
| Date | 2006-05-26 |
| Paper # | NC2006-8 |
| Volume (vol) | vol.106 |
| Number (no) | 79 |
| Page | pp.pp.- |
| #Pages | 6 |
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