Topic Modeling: A Comprehensive Review

Kherwa, Pooja and Bansal, Poonam (2020) Topic Modeling: A Comprehensive Review. EAI Endorsed Transactions on Scalable Information Systems, 7 (24): e2. ISSN 2032-9407

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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.

Item Type: Article
Uncontrolled Keywords: Topic Modeling, Latent Dirichlet Allocation, Latent Semantic Analysis, Inference, Dimension reduction
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 08 Oct 2020 13:52
Last Modified: 08 Oct 2020 13:52
URI: https://eprints.eudl.eu/id/eprint/682

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