Liu, Yuchen, Man, Ka Lok, Li, Gangmin, Payne, Terry 
ORCID: 0000-0002-0106-8731 and Yue, Yong
(2023)
Enhancing Sparse Data Performance in E-Commerce Dynamic Pricing with Reinforcement Learning and Pre-Trained Learning.
In: 2023 International Conference on Platform Technology and Service (PlatCon), 2023-8-16 - 2023-8-18.
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Abstract
This paper introduces a reinforcement learning-based framework designed to tackle dynamic pricing challenges in e-commerce. Prior research has predominantly concentrated on algorithm selection to enhance performance in dense data scenarios. However, many of these models fail to robustly address sparse data structures, such as low-traffic products, leading to the 'cold-start' problem [4]. Through numerical analysis, our framework offers innovative insights derived from the design of the reward function and integrates product clustering with pre-trained learning to mitigate this issue. As a result of this optimization, the performance of predictive models on sparse data is expected to see substantial improvement.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 16 Nov 2023 08:26 |
| Last Modified: | 15 Mar 2024 04:09 |
| DOI: | 10.1109/platcon60102.2023.10255211 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3176820 |
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