Cited By
View all- Li XShen JWang DLu WChen Y(2024)Multi-modal transform-based fusion model for new product sales forecastingEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108606133(108606)Online publication date: Jul-2024
Learning Invariant Representations for New Product Sales Forecasting via Multi-Granularity Adversarial Learning
Authors: 
Zhenzhen Chu, Chengyu Wang, Cen Chen, Dawei Cheng, Yuqi Liang, 
Weining QianAuthors Info & Claims
Zhenzhen Chu, Chengyu Wang, Cen Chen, Dawei Cheng, Yuqi Liang, Weining QianAuthors Info & ClaimsPages 3828 - 3832
Abstract
Sales forecasting during the launch of new products has always been a challenging task, due to the lack of historical sales data. The dynamic market environment and consumer preferences also increase the uncertainty of predictions. Large chains face even greater difficulties due to their extensive presence across various regions. Traditional time-series forecasting methods usually rely on statistical models and empirical judgments, which are difficult to handle large, variable data and often fail to achieve satisfactory performance for new products. In this paper, we propose a Multi-granularity AdversaRial Learning framework (MARL) to leverage knowledge from old products and improve the quality of invariant representations for more accurate sales predictions. To evaluate our proposed method, we conducted extensive experiments on both a real-world dataset from a prominent international Café chain and a public dataset. The results demonstrated that our method is more effective than the existing state-of-the-art baselines for new product sales forecasting.
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Index Terms
- Learning Invariant Representations for New Product Sales Forecasting via Multi-Granularity Adversarial Learning
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Published In
October 2023
5508 pages
ISBN:9798400701245
DOI:10.1145/3583780
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- Frank Hopfgartner,
- Mark Lee,
- Michael Oakes,
- Program Chairs:
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- Min Zhang,
- Rodrygo Santos
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Published: 21 October 2023
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CIKM '23: The 32nd ACM International Conference on Information and Knowledge Management
October 21 - 25, 2023
Birmingham, United Kingdom
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View all- Li XShen JWang DLu WChen Y(2024)Multi-modal transform-based fusion model for new product sales forecastingEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108606133(108606)Online publication date: Jul-2024
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