A method of weight analysis of academic paper authors based on clustering analysis

Abstract

The present invention relates to weight analysis of authors of academic papers, and more particularly, to a method of weight analysis of academic paper authors based on clustering analysis. In the scoring algorithm of the invention, the first author scoring is added with the author citation relation network G, the node2vec is used to model the author citation relation network G to obtain the author's word vector expression, and then the citation relation and the cosine similarity between nodes are used to weigh the scholar's academic scoring, so as to obtain the final scoring; After the experimental demonstration, it is found that the score index obtained in this paper has a higher correlation with h-index, and can weaken some defects of h-index to some extent;; And then according to the author 's word vector expression for clustering, the author' s category and the center of each category are obtained, that is, the author is divided into different segmentation areas. By comparing thedistance between the author's vector and each cluster center, the relative scores in each domain are calculated.

Description

technical field [0001] The present invention relates to weight analysis of authors of academic papers, and more specifically, to a weight analysis method for authors of academic papers based on cluster analysis. Background technique [0002] At present, the h-index algorithm is mainly used to evaluate the academic level of scholars. The success of h-index lies in a basic assumption in the construction of the index, that is, the level of papers can reflect the academic level of scholars to a large extent, and the papers published by scholars Quality should be more important than quantity of papers it publishes. The success of h-index is based on such insights, but due to its relatively simple design, the method has some natural defects, such as insensitivity to time variables, unable to detect the activeness of scholars over time. degree; it is not sensitive to the author’s signature order in the paper, and it is impossible to distinguish the author’s contribution in a paper...

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Problems solved by technology

The success of h-index is based on such insights, but due to its relatively simple design, the method has some natural defects, such as insensitivity to time variables, unable to detect the activeness of scholars over time. degree; it is not sensitive to the author’s signature order in the paper, and it is impossible to distinguish the author’s contribution in a paper (this is of great significance to the academic weight evaluation of scholars); the scoring values ​​​​for different fields cannot be unified, and often appear in the Scholars in one field generally have high h-index values, and scholars in one field generally have low h-index values, which will cause great errors in the evaluation of cross-field authors

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