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A tensor based price evaluation approach for the used mobile phone recycling.
- Source :
-
Expert Systems with Applications . Mar2024:Part E, Vol. 238, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- The automatic price evaluation is an important and challenging issue for the used mobile phone recycling. However, due to complicated relationships between attributes and price as well as insufficient sample data, current approaches cannot achieve accurate price evaluation for the used mobile phones, which significantly reduce the efficiency for the used mobile phone recycling. To this end, a tensor based approach is proposed in this paper, which can achieve accurate and efficient price evaluation for used mobile phones. In the proposed approach, first, the mutual information based attributes selection mechanism and the boxplot based sample selection mechanism are employed to select the most relevant attributes and suitable price samples from used mobile phone dataset. Then, a tensor model is constructed to establish multi-dimensional relationships between selected attributes and prices of used mobile phones. Finally, the missing values in the constructed tensor model is completed through the gradient descent and CANDECOMP/PARAFAC decomposition algorithms. The completed tensor model can be directly used for the price evaluation of used mobile phones based on their attributes without further calculation. Based on the real price dataset of used mobile phones, the experiments indicate that the proposed approach outperforms most of current approaches for the price evaluation for the used mobile phones. • Mutual information is used to select the most relevant attributes. • Boxplot is used to select suitable price samples. • Tensor model is used to establish relationships between attributes and prices. • CP decomposition based algorithm is used to complete missing values in tensor model. • The completed tensor model can be directly used for the price evaluation. [ABSTRACT FROM AUTHOR]
- Subjects :
- *PRICES
*CELL phones
Subjects
Details
- Language :
- English
- ISSN :
- 09574174
- Volume :
- 238
- Database :
- Academic Search Index
- Journal :
- Expert Systems with Applications
- Publication Type :
- Academic Journal
- Accession number :
- 173726986
- Full Text :
- https://doi.org/10.1016/j.eswa.2023.122245