Leveraging Global and Local Topic Popularities for LDA-Based Document Clustering

Leveraging Global and Local Topic Popularities for LDA-Based Document Clustering

Document clustering is of high importance for many natural language technologies. A wide range of computational traditional topic models, such as LDA (Latent Dirichlet Allocation) and its variants, have made great progress. However, traditional LDA-based clustering algorithms might not give good res...

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Bibliographic Details
Main Authors: Peng Yang, Yu Yao, Huajian Zhou
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Document clustering
latent Dirichlet allocation
machine learning
topic modeling
Online Access:https://ieeexplore.ieee.org/document/8970318/

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