2025, Vol. 6, Issue 1, Part I
SUGGESTO: AI powered recommendation system
Author(s): Suguna M, Swasthik K, Veeramanikandan S, Muralidharan S and Krishna Kumar V
Abstract: Personalized product recommendations are a critical component of modern e-commerce, enhancing user experience and business growth. This paper presents SUGGESTO, an AI-powered recommendation system integrating Large Language Models (LLMs), FastAPI for backend management, and. NET WebAssembly for an optimized front-end experience. The system employs a hybrid recommendation approach, combining collaborative filtering, content-based filtering, and deep learning models. It ensures accurate, real-time recommendations based on user behavior, browsing history, and purchase patterns. Experimental results show that our system achieves a 25% improvement in recommendation accuracy and a 30% increase in customer engagement compared to traditional models.
Pages: 815-819 | Views: 62 | Downloads: 38
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How to cite this article:
Suguna M, Swasthik K, Veeramanikandan S, Muralidharan S, Krishna Kumar V. SUGGESTO: AI powered recommendation system. Asian J Manage Commerce 2025;6(1):815-819.
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