Adapting Outperformer from Topic Modeling Methods for Topic Extraction and Analysis: The Case of Afaan Oromo, Amharic, and Tigrigna Facebook Text Comments

naolbakala/Adapting-Outperformer-Topic-Modeling-for-low-resource-Major-Ethiopian-Languages

Topic words based dataset extracted from large size of social media data from three major Ethiopian

AFAAN OROMO SHORT TEXT CLUSTERING USING TOPIC MODELING IN DEEP LEARNING APPROACH

Main Advisor: Mr. Wakgari Dibaba (Ass.Prof ) Text clustering groups texts according to a particular

Short Amharic Text Clustering Using Topic Modeling

Afaan Oromo Facebook posts and comments hate speech dataset

This dataset is collected from Facebook pages those who mainly using Afaan Oromo for their posts. It

A topic modeling approach for analyzing and categorizing electronic healthcare documents in Afaan Oromo without label information

Abstract Afaan Oromo is a resource-scarce language with limited tools developed for its processing,

Topic Modeling for Amharic User Generated Texts

Topic Modeling is a statistical process, which derives the latent themes from extensive collections