Method for predicting author cooperation relation in academic heterogeneous information network

Abstract

The invention discloses a method for predicting an author cooperation relation in an academic heterogeneous information network. The problem about author cooperation relation prediction is solved by utilizing a heterogeneous information network close to a real world. The method comprises the following steps: acquiring the topological attribute of the network according to different measurement of a metapath in the constructed academic heterogeneous information network, introducing concepts of temporal dynamics, transfer similarity and author attribute to acquire the content information of the network, combining the topological attribute and the content information to acquire a characteristic space based on the metapath and the content information, and finding the optimum weight of each characteristic attribute according to the obtained characteristic attribute set and by a logical regression algorithm to predict the author cooperation relation. According to the method, the potential cooperation relation of scholars can be excavated by utilizing academic big data, the scholars can be helped to perform efficient scientific research cooperation and know the academic circle of the scholars, and in particular a good prediction effect on high-yield scholars and high-frequency cooperation relation is achieved.

Description

technical field [0001] The invention relates to a method for predicting author cooperation relationship under an academic heterogeneous information network, in particular to a method for predicting cooperation based on meta-path and content information. Background technique [0002] As scientific research is widely carried out in academia and industry, scholars have created a large number of scientific research results in a steady stream, so academic big data came into being. In academic big data, there are different academic subjects and various academic relationships formed between them, among which the cooperative relationship between scholars is the most common and important, especially in the research of interdisciplinary issues, between scholars from different fields The increasing cooperation among enterprises makes the research on the prediction of cooperative relationship more and more important. However, in the existing technologies, most of the solutions are base...

AI Technical Summary

Problems solved by technology

However, in the existing technologies, most of the solutions are based on isomorphic information networks, and the prediction methods are based on the similarity of nodes, topology and network content information, etc., which cannot well reflect the differences among scholars. The interconnection of the network does not consider the influence of node attributes and network content information on the prediction results.

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