A GraphQL API for Product Recommendation in Women's Clothing Based on Deep Learning Analysis of Product Reviews

Automated Product Recommendation (APR) plays a vital role in modern technology by leveraging Artificial Neural Network (ANN) models powered by deep learning techniques. This study focuses on improving consumer decision-making for women's clothing through an APR system that analyzes review text and approval ratings. GraphQL Application Programming Interface (API) integration facilitates seamless interaction with the recommendation system, allowing efficient querying and retrieval of personalized product recommendations. The developed ANN model showed remarkable effectiveness, achieving an accuracy of 51% in predicting product ratings and an accuracy of 87% in recommending products.