Deep Learning Method for Classifying Items into Categories for Dutch Auctions

Janusz Bobulski; Sabina Szymoniak

doi:10.24423/cames.2024.979

Janusz Bobulski Clemens Adam Mazgaj, Krakow and Department of Computer Science, Czestochowa University of Technology, Czestochowa
Sabina Szymoniak Clemens Adam Mazgaj, Krakow and Department of Computer Science, Czestochowa University of Technology, Czestochowa

DOI: http://dx.doi.org/10.24423/cames.2024.979

Abstract

Artificial Intelligence (AI) methods are widely used in our lives (phones, social media, self-driving cars, and e-commerce). In AI methods, we can find convolutional neural networks (CNN). First of all, we can use these networks to analyze images. This paper presents a method for classifying items into particular categories on an auction site. The technique prompts the seller to which category assign the item when creating a new auction. We choose a neural network with a number of image convolution layers as the best available approach to address this task. All tests were carried out in the Matlab environment using GPU and CPU. Then, the tested and verified solution was implemented in the TensorFlow environment with a CPU processor. Thanks to the cross-validation method, the effectiveness of the recognition system was fully verified in several stages. We obtained promising results. Consequently, we implemented the developed method by adding a new sales offer on the Clemens website.

Keywords

Deep Learning, Internet auction, Classification,

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