CSE 573 Semantic Web Mining: Movie Recommendation System - Spring 2023- Group 31
We use a DNN model to train our Recommender System on MovieLens 100k dataset. The code for the model is present in the code directory. The evaluation folder contains the final results and the recommendation output files for each of our use cases.
Our UI runs on Python, so a complier that can run python is necessary to view the results of our recommender system. The system has three use cases. Recommend movies based on userId, movieId, and genre. Each input by the user followed by a button input will populate a table based on how many desired responses the user indicates.