INFORMATION RESEARCH

Research on Citation Recommendation Based on Text Structure and Citation Motivation

  • Xiong Huixiang ,
  • Huang Xiaojie ,
  • Chen Ziwei ,
  • Xiao Bing ,
  • Chen Qi
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  • School of Information Management, Central China Normal University, Wuhan 430079

Received date: 2022-08-23

  Revised date: 2022-12-24

  Online published: 2023-04-25

Abstract

[Purpose/Significance] Considering the differences of scholars’ citation motivations, a citation recommendation model based on text structure and citation motivation is proposed based on the hierarchical attention network model in deep learning. [Method/Process] By constructing the citation motivation model of researchers, it can be divided into scientific citation motivation and strategic citation motivation. Firstly, the text structure of the paper was mapped to the scientific citation motivation, and the hierarchical attention network model was used to classify chapter contents according to the scientific citation motivation. In addition, the similarity weighted calculation was carried out by the similarity of the paragraphs and the titles, keywords and abstracts of the citing literatures and references, and the recommendation results based on scientific citation motivation were obtained. On this basis, strategic citation motivation was introduced to comprehensively rank the recommendation results to get the final recommendation results. Finally, 1443 references in the field of information science were taken as examples to verify the proposed method. [Result/Conclusion] Experimental results show that this recommendation method achieves citation recommendation based on different motivation of researchers, has certain feasibility and accuracy, and provides reference ideas for subsequent related research.

Cite this article

Xiong Huixiang , Huang Xiaojie , Chen Ziwei , Xiao Bing , Chen Qi . Research on Citation Recommendation Based on Text Structure and Citation Motivation[J]. Library and Information Service, 2023 , 67(8) : 115 -128 . DOI: 10.13266/j.issn.0252-3116.2023.08.011

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