We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Topic Modeling: A Comprehensive Review.
- Authors
Kherwa, Pooja; Bansal, Poonam
- Abstract
Topic modelling is the new revolution in text mining. It is a statistical technique for revealing the underlying semantic structure in large collection of documents. After analysing approximately 300 research articles on topic modeling, a comprehensive survey on topic modelling has been presented in this paper. It includes classification hierarchy, Topic modelling methods, Posterior Inference techniques, different evolution models of latent Dirichlet allocation (LDA) and its applications in different areas of technology including Scientific Literature, Bioinformatics, Software Engineering and analysing social network is presented. Quantitative evaluation of topic modeling techniques is also presented in detail for better understanding the concept of topic modeling. At the end paper is concluded with detailed discussion on challenges of topic modelling, which will definitely give researchers an insight for good research.
- Subjects
TEXT mining; DIRICHLET principle; LATENT semantic analysis; INFERENTIAL statistics; DATA mining
- Publication
EAI Endorsed Transactions on Scalable Information Systems, 2019, Vol 6, Issue 22, p1
- ISSN
2032-9407
- Publication type
Article
- DOI
10.4108/eai.13-7-2018.159623