.png){kind=icon}
返回
Text Mining in Big Data Analytics
.png){kind=icon}
OA
AI
DOI：10.3390/bdcc4010001.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Text mining in big data analytics is emerging as a powerful tool for harnessing the power of unstructured textual data by analyzing it to extract new knowledge and to identify significant patterns and correlations hidden in the data. This study seeks to determine the state of text mining research by examining the developments within published literature over past years and provide valuable insights for practitioners and researchers on the predominant trends, methods, and applications of text mining research. In accordance with this, more than 200 academic journal articles on the subject are included and discussed in this review; the state-of-the-art text mining approaches and techniques used for analyzing transcripts and speeches, meeting transcripts, and academic journal articles, as well as websites, emails, blogs, and social media platforms, across a broad range of application areas are also investigated. Additionally, the benefits and challenges related to text mining are also briefly outlined.
Keyword:
text mining
big data
analytics
review
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
B
IF:
4.4
论文数:
1.3K
被引数:
2.4K
机构
引用论文
Multiscale analysis of architecture, cell size and the cell cortex reveals cortical F-actin density and composition are major contributors to mechanical properties during convergent extension.png)
DevelopmentOAAI
DevelopmentIF0
OAAI分享收藏
Analytical gel permeation chromatography used for preparative fractionation of polymers for degradation studiesPolymer
PolymerIF0
PREAI
分享收藏分享收藏
查看更多内容