Metadata Embeddings for User and Item Cold-start Recommendations

Pre-print available on arXiv.

Structure

1. The paper directory holds the LaTeX source of the paper.
2. The experiments directory holds the code used for experiments.

Reproducing results

To reproduce the results from the paper, do the following.

1. Download and install the LightFM package (pip install lightfm).
2. Download experiment data by running cd experiments/stackoverflow/ && make and cd experiments/movielens/ && make.
3. To run the primary experiment, run ipython -- runner.py --table. This will print LaTeX variable definitions that, when pasted into the paper source file, populate the main results table.
4. To generate the latent dimension sensitivity plots, run ipython -- runner.py --dim --plot. This will take some time.

It is possible to run invididual experiments. Examples:

• ipython -- experiments/stackexchange/model.py --dim 50 --lsi --tags --ids --split 0.2 will run the CrossValidated experiment with 50-dimensional latent space, using the LSI-LR model with both post tags and post ids.
• ipython -- experiments/movielens/model.py --ids --cold --split 0.2 will run the MF model on the MovieLens dataset in the cold-start scenario.