Academic relationship prediction method and device based on neural network introducing semantic information

Abstract

The embodiment of the invention provides an academic relationship prediction method and device based on a neural network introducing semantic information, and the method comprises the steps: determining a node information combination of two to-be-predicted nodes, enabling the node information of scholarship nodes to comprise the scholarship personal information, and enabling the node information of paper nodes to comprise a paper title and a paper abstract; and inputting the node information combination into a relationship prediction model, and outputting a relationship type vector of two nodes. The relationship prediction model is obtained by training based on sample node information and a predetermined relationship type vector label between sample nodes; and the feature vectors of the sample scholarship nodes and the sample paper nodes in training are respectively composed of scholarship personal information features and random additional features, and paper title information features and paper abstract information features. According to the method and the device provided by the embodiment of the invention, paper semantic information is considered, so that the academic relationship prediction accuracy is improved, and more types of academic relationships can be mined.

Description

Technical field[0001]The invention relates to the technical field of academic relationship prediction, in particular to a method and device for academic relationship prediction based on a neural network introducing semantic information.Background technique[0002]In recent years, with the popularization of the mobile Internet and the enrichment of information sources, the unstructured information stored on the Internet has shown an exponential growth trend. Because it is difficult for people to efficiently extract the required structured information from the complex and huge amount of unstructured information, relevant research on network information mining has emerged. Many practical application scenarios in social life, such as polymer compounds, traffic and road networks, academic cooperation networks, biological information, social media networks, etc., can be modeled as pictures by certain means.[0003]By modeling the interaction between entities (nodes) as graphs, the researchers...

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Problems solved by technology

[0013] Embodiments of the present invention provide a method and device for predicting academic relationships based on neural networks that introduce semantic information, to solve the problem of academic relationships caused by the prediction model of neural network-based academic relationship prediction methods in the prior art that cannot take into account the semantic information of papers Problems with low prediction accuracy and few types of relationships that can be mined

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