Fuzzy topic modeling approach for text mining over short text

作者：

Highlights：

• A fuzzy topic modeling method is proposed for short text documents.

• Local and global term frequencies are generated through the bag-of-words model.

• High dimensionality negative effect on global term weighting is eliminated.

• Fuzzy topic modeling approach used for discovering more relevant and precise topics from short text documents.

摘要

•A fuzzy topic modeling method is proposed for short text documents.•Local and global term frequencies are generated through the bag-of-words model.•High dimensionality negative effect on global term weighting is eliminated.•Fuzzy topic modeling approach used for discovering more relevant and precise topics from short text documents.

论文关键词：Topic modeling,Text mining,Short text,LDA,Bag-of-words,Fuzzy c-means,Principal component analysis

论文评审过程：Received 12 January 2019, Revised 2 May 2019, Accepted 14 June 2019, Available online 21 June 2019, Version of Record 21 June 2019.

论文官网地址：https://doi.org/10.1016/j.ipm.2019.102060