Abstract
Recommendation systems have led to the growth of many e-commerce and content providing companies because they perform well in modelling consumer’s habit and providing personalization to users. Recommendation system used in E-commerce has been extensively researched and a number of algorithms/methods have been proposed. These methods can be a linear or a non-linear approach. Neural networks are proven non-linear techniques that outperform the linear techniques and have produced satisfactory results on various available recommendation datasets. Deep learning neural networks have also proven their efficiency in domains such as computer vision and natural language processing and of recent is been applied to recommender systems because of high performance. In this paper, we reviewed deep learning methods that have been applied to recommender systems in E-commerce both in academics and industry.
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Khoali, M., Tali, A., Laaziz, Y. (2021). A Survey of Artificial Intelligence-Based E-Commerce Recommendation System. In: Ben Ahmed, M., Mellouli, S., Braganca, L., Anouar Abdelhakim, B., Bernadetta, K.A. (eds) Emerging Trends in ICT for Sustainable Development. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-53440-0_12
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