Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey

• Published in: Multimedia tools and applications Vol. 78; no. 11; pp. 15169 - 15211
• Main Authors: Jelodar, Hamed, Wang, Yongli, Yuan, Chi, Feng, Xia, Jiang, Xiahui, Li, Yanchao, Zhao, Liang
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2019; Springer Nature B.V
• Subjects: Computer Communication Networks; Computer Science; Data mining; Data Structures and Information Theory; Dirichlet problem; Modelling; Multimedia Information Systems; Researchers; Software engineering; Special Purpose and Application-Based Systems; Topic modeling; Semantic web; Latent Dirichlet allocation; Gibbs sampling; Tag recommendation

Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data and text documents. Researchers have published many articles in the field of topic modeling and applied in various fields such as software engineering, po...