网络安全与数据治理2025，Vol.44Issue(3)：47-53,7.DOI:10.19358/j.issn.2097-1788.2025.03.008
基于改进FP-growth的多品类打包推荐算法
A multi-category bundling recommendation algorithm based on the improved FP-growth algorithm
李雄清 1李永 1王骏飞 1臧凌 1刘德志 2卞宇轩 2柴阅林 2李卓潇 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
Multi-category bundling recommendation is a critical task in modern recommender systems,which aims to combine products from various categories into a one-stop recommendation to meet users'diverse needs and enhance their experience.This task faces challenges such as high demand for real-time responses,large data scale and high data sparsity,which existing bund-ling algorithms struggle to address.This paper proposes a multi-category bundling recommendation algorithm based on an im-proved FP-growth algorithm,which mines associations between product attributes.The algorithm matches the most relevant bun-dling products based on attribute association rules,which effectively alleviates data sparsity under the product view.Experimental results on a dataset from the aviation travel retail sector show that the proposed method significantly improves both bundling quality and efficiency compared to baseline methods.关键词
多品类打包/推荐系统/关联规则挖掘/FP-growth算法/航空旅游零售Key words
multi-category bundling/recommender systems/association rule mining/FP-growth algorithm/aviation travel retail分类
计算机与自动化引用本文复制引用
李雄清,李永,王骏飞,臧凌,刘德志,卞宇轩,柴阅林,李卓潇,刘云韬..基于改进FP-growth的多品类打包推荐算法[J].网络安全与数据治理,2025,44(3):47-53,7.
