Revisiting K-Means and Topic Modeling, a Comparison Study to Cluster Arabic Documents

Revisiting K-Means and Topic Modeling, a Comparison Study to Cluster Arabic Documents

Clustering Arabic text documents is of high importance for many natural language technologies. This paper uses a combined method to cluster Arabic text documents. Mainly, we use generative models and clustering techniques. The study uses latent Dirichlet allocation and k-means clustering algorithm a...

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Bibliographic Details
Main Authors: M. Alhawarat, M. Hegazi
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Clustering text documents
K-means
Arabic language
topic modeling
latent Dirichlet allocation (LDA)
Online Access:https://ieeexplore.ieee.org/document/8402221/

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