计算机与现代化Issue(9)：1-13,13.DOI:10.3969/j.issn.1006-2475.2025.09.001
打包推荐算法综述
Survey on Bundle Recommendation Algorithms
李雄清 1彭明田 1李永 1王骏飞 1刘德志 2卞宇轩 2柴阅林 2刘云韬2
作者信息
- 1. 北京市民航大数据工程技术研究中心,北京 101318||中国民航信息网络股份有限公司,北京 101318
- 2. 北京市民航大数据工程技术研究中心,北京 101318||北京航空航天大学,北京 100191
- 折叠
摘要
Abstract
Bundle recommendation refers to optimizing and recommending the best solution by combining multiple related goods,services,or content,which can meet the various needs of users.With the rapid development of sectors like e-commerce and travel retail,bundle recommendation has become an important approach to improve user experience and business benefits.This paper reviews the research progress and application status of bundle recommendation algorithms.Firstly,the task defini-tion,task characteristics,task challenges,and commonly used evaluation metrics are clarified.The task challenges include the integrity of bundled packages,diversity of bundled packages,data sparsity,cold start problems,and bundle generation prob-lems.Secondly,the existing algorithms are classified into three major categories,data mining-based algorithms,traditional ma-chine learning-based algorithms,deep learning-based algorithms,and further sorted out into seven subcategories.The charac-teristics of each category are thoroughly analyzed.Thirdly,commonly used datasets for the bundle recommendation task are sum-marized.Finally,the future development trends of bundle recommendation are discussed.关键词
打包推荐/组合优化/数据挖掘/深度学习/机器学习Key words
bundle recommendation/combinatorial optimization/data mining/deep learning/machine learning分类
信息技术与安全科学引用本文复制引用
李雄清,彭明田,李永,王骏飞,刘德志,卞宇轩,柴阅林,刘云韬..打包推荐算法综述[J].计算机与现代化,2025,(9):1-13,13.
