A Deep Learning Based Context-Aware Recommendation Library
3rd Year: 1st - 92. A Novel Context Aware Restaurant Recommender System Using Content-Boosted Collaborative Filtering (CACBCF).
UPNEXT: Content-based and Context-Aware Movie Recommender System
This project implements and evaluates ENSFM for recommendation systems on modern, large-scale e-commerce datasets. The research focuses on assessing the scalability, efficiency, and accuracy of ENSFM when applied to real-world datasets from Amazon Books and Yelp
An adaptive e-reader mobile application with music changing based on current text context. Uses AI and NLP to dynamically adjust ongoing soundtrack for enhanced reading immersion.
An advanced hybrid recommendation system that combines collaborative filtering and content-based filtering approaches, enhanced with temporal awareness and contextual personalization
Advanced Data Mining Final Project - March 17, 2022
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