Journal of Soft Computing Paradigm
IRO Journals
Volume 2 — Issue 4 — December 2020

Faultless Decision Making for False Information in Online: A Systematic Approach

https://doi.org/10.36548/jscp.2020.4.004
Yasir Babiker Hamdan
International University of Africa (IUA), Khartoum
A. Sathesh
Department of EEE, Eritrea Institute of Technology
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Hamdan, Yasir Babiker, and A. Sathesh. 2021. “Faultless Decision Making for False Information in Online: A Systematic Approach”. Journal of Soft Computing Paradigm 2 (4): 226-35. https://doi.org/10.36548/jscp.2020.4.004.
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Keywords

— Naive Bayes
— Convolutional Neural Network
— Decision making
Published: 02-01-2021

Abstract

An identifying the news are real or fake instantly with high accuracy is a challenging work. The deep learning algorithm is implementing here to acquire very accurate separation of real and fake news rather than other methods. This research work constructs na誰ve bayes and CNN classifiers with Q-learning decision making. The two different approaches detect fake news in online and it gives to decision making section which is designed at tail in our research. The deep decision making section compares the input and make the decision wisely and it provides the more accurate output rather than single classifiers in deep learning. This research work comprises compare between our proposed works with single classifiers.

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