Analyzing the field of bioinformatics with the multi-faceted topic modeling technique
作者: Go Eun HeoKeun Young KangMin SongJeong-Hoon Lee
作者单位: 1Yonsei University
2POSTECH
刊名: BMC Bioinformatics, 2017, Vol.18 (7)
来源数据库: Springer Journal
DOI: 10.1186/s12859-017-1640-x
关键词: BioinformaticsText miningTopic modelingACT modelKeyphrase extraction
英文摘要: Bioinformatics is an interdisciplinary field at the intersection of molecular biology and computing technology. To characterize the field as convergent domain, researchers have used bibliometrics, augmented with text-mining techniques for content analysis. In previous studies, Latent Dirichlet Allocation (LDA) was the most representative topic modeling technique for identifying topic structure of subject areas. However, as opposed to revealing the topic structure in relation to metadata such as authors, publication date, and journals, LDA only displays the simple topic structure.
原始语种摘要: Bioinformatics is an interdisciplinary field at the intersection of molecular biology and computing technology. To characterize the field as convergent domain, researchers have used bibliometrics, augmented with text-mining techniques for content analysis. In previous studies, Latent Dirichlet Allocation (LDA) was the most representative topic modeling technique for identifying topic structure of subject areas. However, as opposed to revealing the topic structure in relation to metadata such as authors, publication date, and journals, LDA only displays the simple topic structure.
全文获取路径: Springer  (合作)
分享到:
来源刊物:
影响因子:3.024 (2012)

×
关键词翻译
关键词翻译
  • bioinformatics 生物信息学
  • modeling 制祝型
  • topic 话题
  • representative 代理的
  • technique 技术
  • revealing 显色
  • mining 矿业
  • faceted 有小平面的
  • bibliometrics 文献计量学
  • augmented 增加的