Latent Dirichlet Allocation Topic Model
Zou Xiaohu · Intelligent Computer and Applications · 2014
In natural language processing,LDA( Latent Dirichlet Allocation) topic model is a probabilistic model in text semantic mining. LDA is a dimensionality reduction technique to reduce a document represented by words to a random mixture over latent topics,and to realize information retrieval and text categorization. The paper presents the generative process for each document in a corpus and the graphical model representation of LDA. Based on the aboved,the paper also discusses the extended model associated with LDA and the future research trend.