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01-04-2021

Multimodal Price Prediction

Authors: Aidin Zehtab-Salmasi, Ali-Reza Feizi-Derakhshi, Narjes Nikzad-Khasmakhi, Meysam Asgari-Chenaghlu, Saeideh Nabipour

Published in: Annals of Data Science | Issue 3/2023

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Abstract

Price prediction is one of the examples related to forecasting tasks and is a project based on data science. Price prediction analyzes data and predicts the cost of new products. The goal of this research is to achieve an arrangement to predict the price of a cellphone based on its specifications. So, five deep learning models are proposed to predict the price range of a cellphone, one unimodal and four multimodal approaches. The multimodal methods predict the prices based on the graphical and non-graphical features of cellphones that have an important effect on their valorizations. Also, to evaluate the efficiency of the proposed methods, a cellphone dataset has been gathered from GSMArena. The experimental results show 88.3% F1-score, which confirms that multimodal learning leads to more accurate predictions than state-of-the-art techniques.

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Footnotes
2
Cellphone Dataset with 18 Features.
 
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Metadata
Title
Multimodal Price Prediction
Authors
Aidin Zehtab-Salmasi
Ali-Reza Feizi-Derakhshi
Narjes Nikzad-Khasmakhi
Meysam Asgari-Chenaghlu
Saeideh Nabipour
Publication date
01-04-2021
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 3/2023
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-021-00326-z

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