A study on natural language processing neural network with a large knowledge base
Project/Area Number |
24500281
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Sensitivity informatics/Soft computing
|
Research Institution | Keio University |
Principal Investigator |
|
Project Period (FY) |
2012-04-01 – 2016-03-31
|
Project Status |
Completed (Fiscal Year 2015)
|
Budget Amount *help |
¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2013: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2012: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
|
Keywords | ニューラルネットワーク / 知識処理 / 自然言語処理 |
Outline of Final Research Achievements |
We proposed a new natural language processing neural network with association layer and inhibitory layer. It has the following three features. The first one is a regularization of a sentence using a synonym dictionary and N-gram similarity. Owing to this regularization, synonym words are represented as the same neuron. Second feature is the introduction of an association layer based on the co-occurrence frequency database. Owing to this layer, the association between two words can be easily realized. Third one is the introduction of an inhibitory layer. In the application to a question-answering, these neurons can inhibit the membrane potential of neurons which does not relate to the question sentence. Experimental results indicate the effectiveness of the proposed neural network.
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Report
(5 results)
Research Products
(19 results)