Recommendation System using NLP and Vector Databases - Shweiki, Mohammad; Al-Jamal, Basil (جامعة بوليتكنك فلسطين - علم حاسوب, 2024)
This project aims to develop a cutting-edge web application for an online bookstore, featuring an advanced recommendation system to enhance the user experience. utilizing natural language processing (NLP) algorithms, dense vectors, and non-relational databases, this system offers users an intuitive platform to explore a vast collection of books. Users can search for titles based on keywords, authors, or genres, and receive personalized recommendations tailored to their preferences, derived from an analysis of their browsing history, to realize this project, Elastic-Search database was used for storing the documents and related vectors. Angular was used in implementing the frontend while Java Spring Boot was used for the backend.
no of pages 69, علم حاسوب 4/2024
Keywords: Vector Databases; Recommendation Systems; NLP