Using Multi-objective Optimization to Solve the Long Tail Problem in Recommender System

摘要：

　　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 multiobjective 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.

关键词： Recommender system Weighted similarity measure Multi-objective optimization

作者: Jiaona Pang Jun Guo Wei Zhang

作者单位: Department of Computer Science and Technology,East China Normal University,3663 Zhong Shan Rd.N.,Sha Computer Center,East China Normal University,3663 Zhong Shan Rd.N.,Shanghai,China

会议类型: 国际会议

会议名称: The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (第23届亚太知识发现和数据挖掘国际会议(PAKDD2019)

会议地点: 澳门

会议语种:英文

页码: 302-313

在线出版日期: 2019-04-14（万方平台首次上网日期，不代表论文的发表时间）