Transforming E-Commerce with Intelligent Recommendation Systems: A Review of Current Trends in Machine Learning and Deep Learning
DOI:
https://doi.org/10.22399/ijcesen.1183Keywords:
E-commerce, Intelligent Recommendation System, Machine learning, Deep Learning, Artificial Intelligence, Collaborative FilteringAbstract
In the ever-changing realm of E-Commerce, it is essential for online businesses to comprehend and adjust to shifting consumer behaviour in order to achieve long-term success. In which, Intelligent Recommendation System (IRS) has gained familiarity by suggesting personalized information based on user preference and behaviours. Hence, the review paper primarily aims to analyse significance of the intelligent recommendation system to transform ecommerce field, specifically enrich the user personalisation and satisfaction, and enhance revenue in business. Accordingly, the proposed survey is discussed the traditional system and AI-powered personalization system in ecommerce. AI-powered recommendation system utilize sophisticated algorithms to analyse extensive data, allowing for the provision of highly customized and relevant content, product recommendation, and user satisfaction. Besides, it examines future trends in AI integration within e-commerce, particularly advancements in Natural Language Processing (NLP) and visual search technologies, which are poised to further enrich ecommerce. The paper concludes with a look toward future directions for the integration of AI technologies in e-commerce, anticipating advancements in NLP and visual search capabilities, which promise to further enhance the online shopping experience. Overall, the findings of the article underscores the transformative impact of IRS on the e-commerce sector, advocating for their continued development in response to evolving market demands.
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