@inproceedings{b11ba755a9f744249712b4f29e98acd8,
title = "Comparing Recommendation Algorithms in Session-based E-commerce Sites",
abstract = "Recommender systems have become widely used in various website applications. With the integration of deep learning and recommender systems, the classic Session-based Recommender System (SRS) appears, which can obtain implicit feedback from explicit interactions. Some scholars have pro-posed many effective recommendation algorithms to provide better recommendation service in SRS. In order to compare the performance of these session-based recommendation algorithms, we consider a simple E-commerce SRS scenario and choose four representative session-based recommendation algorithms in this paper. Then we do some evaluation experiments. The experimental results show that the combination of local preferences and global preferences will improve the recommendation performance significantly, and for GNNs and RNN s in session recommendation based on deep learning, we also conclude that the prediction effect of GNN s is slightly superior to RNN s on long sessions.",
keywords = "SRS, recommender systems, session-based recommendation algorithms",
author = "Mingtian Peng and Jiahe Zhang and Shilin Wen and Liu, {Chi Harold}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 International Conference on Intelligent Computing, Automation and Systems, ICICAS 2020 ; Conference date: 11-12-2020 Through 13-12-2020",
year = "2020",
month = dec,
doi = "10.1109/ICICAS51530.2020.00085",
language = "English",
series = "Proceedings - 2020 International Conference on Intelligent Computing, Automation and Systems, ICICAS 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "377--380",
editor = "Yun Bai and Diego Cabrera and Qibing Yu and Ziqiang Pu",
booktitle = "Proceedings - 2020 International Conference on Intelligent Computing, Automation and Systems, ICICAS 2020",
address = "United States",
}