Transformer-Based Model for Predicting Customers’ Next Purchase Day in e-Commerce
The paper focuses on predicting the next purchase day (NPD) for customers in e-commerce, a task with applications in marketing, inventory management, and customer retention. A novel transformer-based model for NPD prediction is introduced and compared to traditional methods such as ARIMA, XGBoost, a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
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| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/11/11/210 |
| _version_ | 1797459684754456576 |
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| author | Alexandru Grigoraș Florin Leon |
| author_facet | Alexandru Grigoraș Florin Leon |
| author_sort | Alexandru Grigoraș |
| collection | DOAJ |
| description | The paper focuses on predicting the next purchase day (NPD) for customers in e-commerce, a task with applications in marketing, inventory management, and customer retention. A novel transformer-based model for NPD prediction is introduced and compared to traditional methods such as ARIMA, XGBoost, and LSTM. Transformers offer advantages in capturing long-term dependencies within time series data through self-attention mechanisms. This adaptability to various time series patterns, including trends, seasonality, and irregularities, makes them a promising choice for NPD prediction. The transformer model demonstrates improvements in prediction accuracy compared to the baselines. Additionally, a clustered transformer model is proposed, which further enhances accuracy, emphasizing the potential of this architecture for NPD prediction. |
| first_indexed | 2024-03-09T16:54:58Z |
| format | Article |
| id | doaj.art-a6554187b8fe4476a91602d64c645080 |
| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-03-09T16:54:58Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-a6554187b8fe4476a91602d64c6450802023-11-24T14:36:20ZengMDPI AGComputation2079-31972023-10-01111121010.3390/computation11110210Transformer-Based Model for Predicting Customers’ Next Purchase Day in e-CommerceAlexandru Grigoraș0Florin Leon1Faculty of Automatic Control and Computer Engineering, “Gheorghe Asachi” Technical University of Iasi, Bd. Mangeron 27, 700050 Iasi, RomaniaFaculty of Automatic Control and Computer Engineering, “Gheorghe Asachi” Technical University of Iasi, Bd. Mangeron 27, 700050 Iasi, RomaniaThe paper focuses on predicting the next purchase day (NPD) for customers in e-commerce, a task with applications in marketing, inventory management, and customer retention. A novel transformer-based model for NPD prediction is introduced and compared to traditional methods such as ARIMA, XGBoost, and LSTM. Transformers offer advantages in capturing long-term dependencies within time series data through self-attention mechanisms. This adaptability to various time series patterns, including trends, seasonality, and irregularities, makes them a promising choice for NPD prediction. The transformer model demonstrates improvements in prediction accuracy compared to the baselines. Additionally, a clustered transformer model is proposed, which further enhances accuracy, emphasizing the potential of this architecture for NPD prediction.https://www.mdpi.com/2079-3197/11/11/210e-commercetransformerforecastingtime seriesnext purchase day |
| spellingShingle | Alexandru Grigoraș Florin Leon Transformer-Based Model for Predicting Customers’ Next Purchase Day in e-Commerce Computation e-commerce transformer forecasting time series next purchase day |
| title | Transformer-Based Model for Predicting Customers’ Next Purchase Day in e-Commerce |
| title_full | Transformer-Based Model for Predicting Customers’ Next Purchase Day in e-Commerce |
| title_fullStr | Transformer-Based Model for Predicting Customers’ Next Purchase Day in e-Commerce |
| title_full_unstemmed | Transformer-Based Model for Predicting Customers’ Next Purchase Day in e-Commerce |
| title_short | Transformer-Based Model for Predicting Customers’ Next Purchase Day in e-Commerce |
| title_sort | transformer based model for predicting customers next purchase day in e commerce |
| topic | e-commerce transformer forecasting time series next purchase day |
| url | https://www.mdpi.com/2079-3197/11/11/210 |
| work_keys_str_mv | AT alexandrugrigoras transformerbasedmodelforpredictingcustomersnextpurchasedayinecommerce AT florinleon transformerbasedmodelforpredictingcustomersnextpurchasedayinecommerce |