Online purchase decisions for tourism e-commerce

作者：

Highlights：

• This study is performed by means of the clickstream data from an e-tourism site.

• An emprical analysis is conducted to reveal purchase patterns for tourism products.

• A novel learning model called co-EM-LR is proposed for online purchase prediction.

• Extensive experiments are conducted to validate the superiority of co-EM-LR model.

摘要

•This study is performed by means of the clickstream data from an e-tourism site.•An emprical analysis is conducted to reveal purchase patterns for tourism products.•A novel learning model called co-EM-LR is proposed for online purchase prediction.•Extensive experiments are conducted to validate the superiority of co-EM-LR model.

论文关键词：Purchase prediction,Tourism E-commerce,Clickstream data,Classification,Logistic regression,Semi-supervised learning,Multi-view learning

论文评审过程：Received 9 April 2019, Revised 9 July 2019, Accepted 11 August 2019, Available online 25 September 2019, Version of Record 3 October 2019.

论文官网地址：https://doi.org/10.1016/j.elerap.2019.100887