Presentation | 1999/3/5 From word representation vectors to phrase representation vectors Naoto TAKAHASHI, Minoru MOTOKI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Miikkulainen extended back-propagation to modify not only link weights but also input signals given to neural networks. He trained his neural network, ca11ed FGREP, with this "extened back-propagation" to learn case-role assignment, and showed that FGREP acquired vectorial respresentations of words based on a corpus.The authors modified the output format of FGREP so that the learning becomes faster and more stable. We also added two additional networks so that noun phrases of the form "adjective+noun" are accepted as syntactic constituent of the input sentence, in addition to simple nouns. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | semantic representation form / neural network / FGREP / case-role assignment / auto-association |
Paper # | TL98-21 |
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Committee | TL |
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Conference Date | 1999/3/5(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Thought and Language (TL) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | From word representation vectors to phrase representation vectors |
Sub Title (in English) | |
Keyword(1) | semantic representation form |
Keyword(2) | neural network |
Keyword(3) | FGREP |
Keyword(4) | case-role assignment |
Keyword(5) | auto-association |
1st Author's Name | Naoto TAKAHASHI |
1st Author's Affiliation | Machine Understanding Division, Electrotechnical Laboratory() |
2nd Author's Name | Minoru MOTOKI |
2nd Author's Affiliation | Faculty of Engineering Kyushu Sangyo University |
Date | 1999/3/5 |
Paper # | TL98-21 |
Volume (vol) | vol.98 |
Number (no) | 640 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |