Hierarchical topic modeling with automatic knowledge mining

作者：

Highlights：

• Propose a novel knowledge-based hierarchical topic model.

• Propose a learning algorithm that continuously improves the results.

• Design a hierarchical structure to maintain knowledge.

• Propose the parameter estimation method based on Gibbs sampling.

摘要

•Propose a novel knowledge-based hierarchical topic model.•Propose a learning algorithm that continuously improves the results.•Design a hierarchical structure to maintain knowledge.•Propose the parameter estimation method based on Gibbs sampling.

论文关键词：Hierarchical topic modeling,Text mining,Knowledge mining,Non-parametric Bayesian learning,Gibbs sampling

论文评审过程：Received 15 October 2017, Revised 28 January 2018, Accepted 6 March 2018, Available online 7 March 2018, Version of Record 20 March 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.008