@inproceedings{cf262556c2ed4b2aa2ef398a2f80cdeb,
title = "Why you should listen to this song: Reason generation for explainable recommendation",
abstract = "Explainable recommendation, which makes a user aware of why such items are recommended has received a lot of attention as a highly practical research topic. The goal of our research is to make the users feel as if they are receiving recommendations from their friends. To this end, we formulate a new challenging problem called reason generation for explainable recommendation in conversation applications, and propose a solution that generates a natural language explanation of the reason for recommending an item to that particular user. Evaluation with manual assessments indicates that our generated reasons are relevant to songs and personalized to users. They are also fluent and easy to understand. A large-scale online experiments show that our method outperforms manually selected reasons by 8.2\% in terms of click-through rate.",
keywords = "Conversational recommendation, explainable recommendation, natural language generation, personalization, recommender system",
author = "Guoshuai Zhao and Hao Fu and Ruihua Song and Tetsuya Sakai and Xing Xie and Xueming Qian",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 18th IEEE International Conference on Data Mining Workshops, ICDMW 2018 ; Conference date: 17-11-2018 Through 20-11-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/ICDMW.2018.00187",
language = "英语",
series = "IEEE International Conference on Data Mining Workshops, ICDMW",
publisher = "IEEE Computer Society",
pages = "1316--1322",
editor = "Hanghang Tong and Zhenhui Li and Feida Zhu and Jeffrey Yu",
booktitle = "Proceedings - 18th IEEE International Conference on Data Mining Workshops, ICDMW 2018",
}