@inproceedings{aa4cc4c1517845dea40085c0727d07c0,
title = "Using multi-objective optimization to solve the long tail problem in recommender system",
abstract = "An improved algorithm for recommender system is proposed in this paper where not only accuracy but also comprehensiveness of recommendation items is considered. We use a weighted similarity measure based on non-dominated sorting genetic algorithm II (NSGA-II). The solution of optimal weight vector is transformed into the multi-objective optimization problem. Both accuracy and coverage are taken as the objective functions simultaneously. Experimental results show that the proposed algorithm improves the coverage while the accuracy is kept.",
keywords = "Multi-objective optimization, Recommender system, Weighted similarity measure",
author = "Jiaona Pang and Jun Guo and Wei Zhang",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019 ; Conference date: 14-04-2019 Through 17-04-2019",
year = "2019",
doi = "10.1007/978-3-030-16142-2\_24",
language = "英语",
isbn = "9783030161415",
series = "Lecture Notes in Computer Science",
publisher = "Springer Verlag",
pages = "302--313",
editor = "Qiang Yang and Zhi-Hua Zhou and Zhiguo Gong and Min-Ling Zhang and Sheng-Jun Huang",
booktitle = "Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Proceedings",
address = "德国",
}