%A Lu Wanhui,Tan Zongying %T Measuring Novelty of Scholarly Articles %0 Journal Article %D 2018 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2017.1012 %P 22-29 %V 2 %N 3 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4481.shtml} %8 2018-03-25 %X

[Objective] This paper aims to construct a novelty index to evaluate the academic achievements. [Methods] First, we proposed a model to calculate content eigenfactor based on deep learning (Doc2Vec) and Hidden Markov Model. Then, we built the topic novelty measure index. Finally, we examined the proposed method with academic papers published by three Chinese LIS journals in 2014. [Results] Compared with the existing methods, the proposed model measured the topic novelty more effectively. [Limitations] Our empirical research only examined abstracts of the academic papers. [Conclusions] The proposed method could help us evaluate and monitor scholarly research.