中华医学图书情报杂志2018，Vol.27Issue(2)：20-25,6.DOI:10.3969/j.issn.1671-3982.2018.02.004
医学文献主题新颖性探测方法对比分析
Comparative analysis of subject novelty detection methods in medical literature
陈斯斯 1董立平 1许丹 1郭继军1
作者信息
- 1. 中国医科大学图书馆,辽宁 沈阳 110122
- 折叠
摘要
Abstract
Objective To study the feasibility of novelty detection model in assessing the subject novelty of medical literature and comparatively analyze the advantages and disadvantages of words-overlap algorithm and co-words-based inverse file frequency quantitative algorithm. Methods Two novelty detection models were established for the 8 research subjects in PubMed-covered literature. The feasibility of two novelty detection models in assessing the subject novelty of medical literature was assessed according to the subject novelty of literature analyzed by experts, ROC curves and AUC values. Results Words-overlap algorithm showed that the fluctuating amplitude of subject novelty was rather high, which can thus reflect the difference between the contents in literature on the data. ROC curves and AUC values-based analysis revealed a high accuracy of words-overlap algorithm for judging the novelty of literature while co-words-based inverse file frequency quantitative algorithm displayed a low accuracy for judging the novelty of literature. Conclusion The novelty of literature detected with the two novelty detection methods is moderately related. The mean novelty value detected with the two novelty detection methods is of statistical signifi-cance. However, the novelty of literature detected with words-overlap algorithm is higher than that detected with co-words-based inverse file frequency quantitative algorithm.关键词
文献主题/新颖性探测/ROC曲线/可行性分析Key words
Subject of literature/Novelty detection/ROC curve/Feasibility analysis分类
社会科学引用本文复制引用
陈斯斯,董立平,许丹,郭继军..医学文献主题新颖性探测方法对比分析[J].中华医学图书情报杂志,2018,27(2):20-25,6.
