Hybrid Collaborative Recommendation via Semi-AutoEncoder
Information Retrieval
2017-08-17 v2
Abstract
In this paper, we present a novel structure, Semi-AutoEncoder, based on AutoEncoder. We generalize it into a hybrid collaborative filtering model for rating prediction as well as personalized top-n recommendations. Experimental results on two real-world datasets demonstrate its state-of-the-art performances.
Keywords
Cite
@article{arxiv.1706.04453,
title = {Hybrid Collaborative Recommendation via Semi-AutoEncoder},
author = {Shuai Zhang and Lina Yao and Xiwei Xu and Sen Wang and Liming Zhu},
journal= {arXiv preprint arXiv:1706.04453},
year = {2017}
}
Comments
9 pages, ICONIP 2017