Comparison of performance evaluation of the baseline and hybrid recommendation systems using various metrics, to prove that hybrid systems perform better. We used movielens 100k dataset from movielens website.
Requirements: Python 3.7 Numpy 1.14.6 pandas 1.0.1 matplotlib surprise 1.1 sklearn 0.22 lightfm 1.15
Installation statements: pip install numpy pip install pandas pip install matplotlib pip install scikit-surprise pip install sklearn pip install lightfm
Dataset: Movielens and IMDB datasets are present in input folder. Check if the input folder exists. If not present, create a folder 'input' and copy the input files to this location. Download the dataset from https://grouplens.org/datasets/movielens/latest/, https://www.kaggle.com/stefanoleone992/imdb-extensive-dataset
Four models in four different files: BaselineKNN.py BaselineSVD++.py ProposedHybridSVDContent.py ProposedLightFM.py
After installing all the required libraries and placing the files in the input folder, run the files using below statements:
python BaselineKNN.py python BaselineSVD++.py python ProposedHybridSVDContent.py python ProposedLightFM.py