Tuning Word2vec for Large Scale Recommendation Systems

@article{Chamberlain2020TuningWF,
  title={Tuning Word2vec for Large Scale Recommendation Systems},
  author={Benjamin Paul Chamberlain and Emanuele Rossi and Dan Shiebler and Suvash Sedhain and Michael M. Bronstein},
  journal={Proceedings of the 14th ACM Conference on Recommender Systems},
  year={2020}
}
Word2vec is a powerful machine learning tool that emerged from Natural Language Processing (NLP) and is now applied in multiple domains, including recommender systems, forecasting, and network analysis. As Word2vec is often used off the shelf, we address the question of whether the default hyperparameters are suitable for recommender systems. The answer is emphatically no. In this paper, we first elucidate the importance of hyperparameter optimization and show that unconstrained optimization… 

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