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Academic social network scientific research partner recommending method

A technology for scientific research collaborators and social networks, applied in the field of academic social network research collaborators recommendation, which can solve the problem of only considering collaborators

Inactive Publication Date: 2018-03-23
GUANGXI NORMAL UNIV
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Problems solved by technology

[0008] The present invention aims to solve the problem that existing collaborator recommendation methods for academic social networks only consider the relationship between collaborators, resulting in invalid recommendations, and provides a method for recommending collaborators in academic social networks

Method used

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  • Academic social network scientific research partner recommending method
  • Academic social network scientific research partner recommending method
  • Academic social network scientific research partner recommending method

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Embodiment Construction

[0033] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific examples and accompanying drawings.

[0034] The present invention provides a method for recommending collaborators in an academic social network based on a tag along the walk for collaborators in an academic social network, such as figure 1 As shown, by constructing an abstract graph of academic social cooperation, and using machine learning methods to classify and add labels to researchers' academic paper information, and then perform random walks on the academic cooperation graph to change the Markov chain using label attribute information The transition probability matrix in the stochastic algorithm of the model allows for more accurate recommendations.

[0035] First, the original data is abstracted into the form of an academic cooperation graph. The original data is a DBLP d...

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Abstract

The present invention discloses an academic social network scientific research partner recommending method. The method comprises the steps of adopting a machine learning decision tree model to classify the scientific research worker nodes and adding the labels, utilizing two novel evaluation indexes of the activity degree and the academic level to change the weights of the nodes, adopting the random walk to calculate the similarity between the nodes, etc. In order to solve the invalid partner recommending problems, especially under the academic big data background, the method of the present invention utilizes a method of combining the random walk added the weight and the decision tree model to enable the random walk to become more tendentious and to walk to the most valuable potential partner node, thereby providing the most suitable partner to the scientific research workers.

Description

technical field [0001] The invention relates to the technical field of social networks, in particular to a method for recommending scientific research collaborators in an academic social network. Background technique [0002] A social network can be abstractly described as a graph composed of many nodes, and the edges between the nodes represent the connections between them, such as the fan relationship in Weibo. Academic Social Network is a kind of social network, in which nodes represent academic researchers, and edges between nodes represent cooperative relationships. According to the analysis of academic big data by researchers, it is found that academic papers have been prolific in recent years. A large part of the reason is that researchers prefer to publish papers in a collaborative way, such as institutions and institutions, schools and schools. , or between researchers and researchers. Therefore, the need to recommend academic collaborators has received great atte...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/00G06N99/00
CPCG06Q50/01G06N20/00
Inventor 李先贤郭亚萌王利娥刘鹏
Owner GUANGXI NORMAL UNIV
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