Development of Machine Learning-Based Text Processing Tool for Abstract of Physical Chemistry Papers

被引：0
|
作者：
Watari, Yuika
Okuwaki, Koji
Mochizuki, Yuji
机构：
来源：
JOURNAL OF COMPUTER CHEMISTRY-JAPAN | 2019年 / 18卷 / 03期
关键词：
Text processing; Machine learning; Doc2Vec; Degree of similarity;
D O I：
10.2477/jccj.2019-0012
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
We have developed a text processing tool consisting of several machine learning-related programs such as TreeTagger and Doc2Vec. This system was applied to a number of abstracts of a couple of physical chemistry journals (Chemical Physics Letters and American Journal of Physics). The degree of similarity of contents was then made evaluatable as a guide for papers to be checked for a certain topic.
引用
收藏
页码：123 / 125
页数：3
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