Tea in benefits of health: A literature analysis using text mining and latent dirichlet allocation

Ching Hsue Cheng, Wei Lun Hung

研究成果: 書貢獻/報告類型會議貢獻

2 引文 斯高帕斯(Scopus)

摘要

Tea originated in Asian, which was initially used as a medicinal herb. The variety of tea is according to different manufacturing processes and levels of oxidation. The different varieties of tea have different level of effects on health, thus this study adopted text mining technique and Latent Dirichlet Allocation (LDA) to analyze literature for tea in health effect. This study chose Web of Science as the database of literature source, and the search literature from 2007 to 2017. The total 1230 journal articles were collected in this study. The title, abstract, and keywords of the collected journal articles were used as a dataset for the experiment. Experimental results show that the VEM method is significantly lower than Gibbs sampling in perplexity. Hence, this study chooses K=150 when VEM method and Gibbs sampling reach the minimal perplexity in the same time. Many topics that related with tea and compounds of tea, however some topics had terms that related to health and disease. The top 10 topics show that tea could reduce the risk of diseases and benefit of health.

原文英語
主出版物標題ICMHI 2018 - Proceedings of 2018 the 2nd International Conference on Medical and Health Informatics
發行者Association for Computing Machinery (ACM)
頁面148-155
頁數8
ISBN(電子)9781450363891
DOIs
出版狀態已發佈 - 六月 8 2018
對外發佈Yes
事件2nd International Conference on Medical and Health Informatics, ICMHI 2018 - Tsukuba, 日本
持續時間: 六月 8 2018六月 10 2018

出版系列

名字ACM International Conference Proceeding Series

會議

會議2nd International Conference on Medical and Health Informatics, ICMHI 2018
國家日本
城市Tsukuba
期間6/8/186/10/18

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

指紋 深入研究「Tea in benefits of health: A literature analysis using text mining and latent dirichlet allocation」主題。共同形成了獨特的指紋。

引用此