JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2016, Vol. 51 ›› Issue (5): 94-101.doi: 10.6040/j.issn.1671-9352.1.2015.E15

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Knowledge vein-based recommendation of academic papers

TAN Hong-ye1, YAO Yi-lu1, LIANG Ying-hong2   

  1. 1.School of Computer and Information Technology, Shanxi University, Taiyuan 030006, Shanxi, China;
    2.School of Software Engineering, Jinling Institute of Technology, Nanjing 211169, Jiangsu, China
  • Received:2015-09-25 Online:2016-05-20 Published:2016-05-16

Abstract: This paper proposed a method of scientific papers recommendation based on knowledge vein, which identified the authors of paper with their keywords and build a knowledge vein by using the synonymy, hyponymy and co-occurrence relationship of keywords. This method recommended academic papers for authors combined with CBF and knowledge vein. This method definition that similarity between authors and papers is the average maximum semantic similarity of the keyword vectors. Currently this article considered two kinds of semantic relations, synonymous and hyponymy. In addition, the relation of co-occurrence also was considered. The results showed that this method can provide more accurate and credible scientific paper recommendation service for authors.

Key words: knowledge vein, interest model, relation extraction, paper recommendation

CLC Number: 

  • TP391
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