Abstract
The large array of recommendation algorithms proposed over the years brings a challenge in reproducing and comparing their performance. This paper introduces an open-source Java library that implements a suite of state-of-the-art algorithms as well as a series of evaluation metrics. We empirically find that LibRec performs faster than other such libraries, while achieving competitive evaluative performance.
| Original language | English |
|---|---|
| Number of pages | 4 |
| Journal | CEUR Workshop Proceedings |
| Volume | 1388 |
| Publication status | Published - 1 Jul 2015 |
| Externally published | Yes |
| Event | 23rd Conference on User Modeling, Adaptation, and Personalization, UMAP 2015 - Dublin, Ireland Duration: 29 Jun 2015 → 3 Jul 2015 |