Vahid Heidari - School of Engineering Science, University of Tehran, Tehran, Iran,
Seyed Mahmoud Taheri - School of Engineering Science, University of Tehran, Tehran, Iran,

In this paper, we investigate two versions of unsupervised clustering Latent Dirichlet Allocation (LDA) methods in original and fuzzy forms. Gibbs samplers are implemented for examining clustering performances on Persian news dataset. Our experimental results are showed that the fuzzy implementation of LDA performs better in text clustering tasks

Fuzzy Bag of Words, Fuzzy Latent Dirichlet Allocation (FLDA), Natural Language Processing, Text Mining.