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Network embedding learning method based on topology perception text representation

A learning method and representation technology, which can be used in biological neural network models, unstructured text data retrieval, text database browsing/visualization, etc. , the effect of performance improvement

Active Publication Date: 2021-07-13
SUN YAT SEN UNIV
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  • Application Information

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Problems solved by technology

These methods can achieve good results on small networks, but due to the high complexity of the algorithm, they are not suitable for large networks.

Method used

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  • Network embedding learning method based on topology perception text representation
  • Network embedding learning method based on topology perception text representation
  • Network embedding learning method based on topology perception text representation

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Embodiment Construction

[0038] The accompanying drawings are for illustrative purposes only and cannot be construed as limiting the patent;

[0039] In order to better illustrate this embodiment, some parts in the drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0040] For those skilled in the art, it is understandable that some well-known structures and descriptions thereof may be omitted in the drawings.

[0041] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0042] Such as Figure 1-2 As shown, a network embedding learning method based on topology-aware text representation includes the following steps:

[0043] S1: Use the graph neural network to extract the local topology information of the nodes in the text network, and obtain the topology representation of all nodes;

[0044] S2: Input the topology representation of the node obtained in S1 to...

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Abstract

The invention provides a network embedding learning method based on topology perception text representation, which comprises the following steps of: adaptively generating a topology perception filter by using local topology structure information of a node, and learning the text representation so as to obtain the topology perception text representation. Topological structure information is more effectively fused into mining of text representation; besides, the method can be combined with an existing network embedding model based on context awareness, the application range is wider, the performance of link prediction and node classification tasks is improved, and the effectiveness of network node representation learned by the method is reflected.

Description

technical field [0001] The present invention relates to the field of network embedding methods, and more specifically, to a network embedding learning method based on topology-aware text representation. Background technique [0002] In the real world, data with a network structure is very common, for example, social networks based on Weibo, WeChat and other platforms, paper citation networks, etc. These networks often contain a large amount of information. Reasonable and effective mining of this information is very beneficial to the application of some downstream tasks, such as product recommendation in e-commerce systems and related paper recommendation. In today's era of explosive growth in the amount of information, these networks usually contain a large number of nodes and edges, and the scale is very large. Direct processing of the network requires a lot of time and storage space, and the calculation efficiency is very low. Therefore, it is of great significance to stu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/901G06F16/906G06F16/34G06N3/04
CPCG06F16/9024G06F16/906G06F16/345G06N3/045Y02D30/70
Inventor 苏勤亮陈佳星
Owner SUN YAT SEN UNIV
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