Parameterized paper network node representing learning method
A learning method and network node technology, applied in neural learning methods, biological neural network models, data processing applications, etc., can solve the problem that new papers cannot perform representation learning and so on
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[0181] In this embodiment, the Cora paper data set and the Pubmed knowledge network data set are used for learning and experimental work.
[0182] Cora is a paper data set containing a total of 2708 paper nodes, including 2708 nodes and 5429 edges. Each node corresponds to a paper rich text information vector with a length of 1433. The rich text information vector is represented by 0 / 1 whether the word is exist. At the same time, each node is associated with a class attribute, and the total number of class attribute values is 7.
[0183] Pubmed is a knowledge network dataset containing a total of 19,717 paper nodes, including 19,717 nodes and 44,338 edges. Each node corresponds to a paper-rich text information vector with a length of 500. The rich text information vector is represented by 0 / 1 word does it exist. At the same time, each node is associated with a class attribute, and the total number of class attribute values is 3.
[0184] In order to verify the effective...
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