A Novel Two-Fold Loss Function for Data Clustering and Reconstruction: Application to Document Analysis

A Novel Two-Fold Loss Function for Data Clustering and Reconstruction: Application to Document Analysis

In the midst of the ongoing COVID-19 pandemic, there has been a surge in scientific literature aimed at understanding the virus and its impact. However, it has become challenging for a researcher to deal with thousands of articles published daily. This paper proposes a novel deep-learning architectu...

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Bibliographic Details
Main Authors: Mebarka Allaoui, Mohammed Lamine Kherfi, Oussama Aiadi, Samir Brahim Belhaouari
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Clustering
COVID-19
deep learning
dimensionality reduction
document organization
topic modeling
Online Access:https://ieeexplore.ieee.org/document/10242111/

Internet

https://ieeexplore.ieee.org/document/10242111/

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