English

SweetRS: Dataset for a recommender systems of sweets

Information Retrieval 2017-09-13 v1

Abstract

Benchmarking recommender system and matrix completion algorithms could be greatly simplified if the entire matrix was known. We built a \url{sweetrs.org} platform with 7777 candies and sweets to rank. Over 20002000 users submitted over 4400044000 grades resulting in a matrix with 28%28\% coverage. In this report, we give the full description of the environment and we benchmark the \textsc{Soft-Impute} algorithm on the dataset.

Keywords

Cite

@article{arxiv.1709.03496,
  title  = {SweetRS: Dataset for a recommender systems of sweets},
  author = {Łukasz Kidziński},
  journal= {arXiv preprint arXiv:1709.03496},
  year   = {2017}
}

Comments

2 pages, 1 figure