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Detecting Anomalies in Advertising Web Traffic with the Use of the Variational Autoencoder Cover

Detecting Anomalies in Advertising Web Traffic with the Use of the Variational Autoencoder

Journal of Artificial Intelligence and Soft Computing Research
Volume 12 (2022): Issue 4 (October 2022)
By: Marcin Gabryel,  Dawid Lada,  Zbigniew Filutowicz,  Zofia Patora-Wysocka,  Marek Kisiel-Dorohinicki and  Guang Yi Chen  
Open Access
|Oct 2022

Authors

Marcin Gabryel

marcin.gabryel@pcz.pl

Department of Intelligent Computer Systems, Częstochowa University of Technology, Częstochowa, Poland

Dawid Lada

Spark Digitup, Krakow, Poland

Zbigniew Filutowicz

Institute of Information Technologies, University of Social Sciences, Lodz

Zofia Patora-Wysocka

Management Department, University of Social Science, Lodz, Poland

Marek Kisiel-Dorohinicki

Institute of Computer Science, AGH University of Science and Technology, Krakow, Poland

Guang Yi Chen

Department of Computer Science and Software Engineering Concordia University, Canada
DOI: https://doi.org/10.2478/jaiscr-2022-0017
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Language: English
Page range: 255 - 256
Submitted on: Apr 2, 2022
|
Accepted on: Oct 12, 2022
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Published on: Oct 29, 2022
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
anomaly detection,
web traffic,
ad fraud,
variational autoencoder
Related subjects:
Computer sciences,
Artificial intelligence,
Databases and data mining

© 2022 Marcin Gabryel, Dawid Lada, Zbigniew Filutowicz, Zofia Patora-Wysocka, Marek Kisiel-Dorohinicki, Guang Yi Chen, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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