Deep hybrid collaborative filtering for Web service recommendation

作者：

Highlights：

• Proposing a novel deep learning based hybrid service recommendation approach.

• Capturing non-linear interactions between mashups and their component services.

• Evaluating pointwise and pairwise loss functions in the recommendation task.

• The approach outperforms state-of-the-art methods on a real-world dataset.

摘要

•Proposing a novel deep learning based hybrid service recommendation approach.•Capturing non-linear interactions between mashups and their component services.•Evaluating pointwise and pairwise loss functions in the recommendation task.•The approach outperforms state-of-the-art methods on a real-world dataset.

论文关键词：Web service recommendation,Mashup,Collaborative filtering,Deep learning

论文评审过程：Received 27 September 2017, Revised 29 May 2018, Accepted 30 May 2018, Available online 5 June 2018, Version of Record 18 June 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.05.039