Presentation 2004/3/10
A proposal of 3-dimensional self organizing memory and its application to knowledge extraction from natural language
Kai SAKAKIBARA, Masafumi HAGIWARA,
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Abstract(in English) In this papaer, we propose a 3-dimentional self organizing memory and describe its application to knowledge extraction from natural language. First, proposed system extracts a relation between words by JUMAN (Morpheme Analysis System) and KNP (Syntax Analysis System), and stores it in short term memory. In the short term memory, relations are attenuated with the passage of process. However, relations with high frequency of appearance are stored in long term memory without attenuation. The relations in the long term memory are arranged by the proposed 3-dimensial self organizing memory. We used new learning algorithm called "Potential Firing" in the learning phase. In the recall phase, proposed system recalls relational knowledge from learned knowledge based on input sentence. We used new recall algorithm called "Waterfall Recall" in the recall phase. We added a function to respond to questions in natural language with "Yes/No". We valuate the quantity of correct answer to confirm the validity of proposed system.
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Keyword(in English) Knowledge representation / Natural language processing / 3-dimensional self organizing memory
Paper # NC2003-145
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Conference Information
Committee NC
Conference Date 2004/3/10(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A proposal of 3-dimensional self organizing memory and its application to knowledge extraction from natural language
Sub Title (in English)
Keyword(1) Knowledge representation
Keyword(2) Natural language processing
Keyword(3) 3-dimensional self organizing memory
1st Author's Name Kai SAKAKIBARA
1st Author's Affiliation Department of Information and Computer Science, Faculty of Science and Technology, Keio University()
2nd Author's Name Masafumi HAGIWARA
2nd Author's Affiliation Department of Information and Computer Science, Faculty of Science and Technology, Keio University
Date 2004/3/10
Paper # NC2003-145
Volume (vol) vol.103
Number (no) 732
Page pp.pp.-
#Pages 6
Date of Issue