基于萤火虫聚类的协同过滤推荐算法  

Collaborative Filtering Recommendation Algorithm Based on Firefly Clustering

作　　者：魏涛 刘亚军[1] 叶传标[1] 曹阳[1] WEI Tao;LIU Ya-jun;YE Chuan-biao;CAO Yang(College of Computer Science and Technology,Sanjiang University,Nanjing 210012,China)

机构地区：[1]三江学院计算机科学与工程学院

出　　处：《电脑知识与技术》2019年第11X期289-291,共3页Computer Knowledge and Technology

摘　　要：针对基于聚类的协同过滤推荐算法在进行聚类代价函数优化时容易陷入局部最优的问题,将具有良好全局最优搜索能力的萤火虫优化算法与聚类算法相互结合,提出一种基于萤火虫聚类的协同过滤推荐算法,实验结果表明,所提出的算法优于基于聚类的协同过滤推荐算法,其推荐准确率更高,完成实时推荐所花费的时间更少。Aiming at the problem that the collaborative filtering recommendation algorithm Based on clustering is apt to fall into local optimum during optimizing of the clustering cost function,a collaborative filtering recommendation algorithm Based on firefly clustering is proposed,which combines the firefly optimization algorithm and the clustering algorithm with good global optimum search ability.The experimental results show that the proposed algorithm is better than that the collaborative filtering recommendation algorithm Based on clustering,which has higher recommendation accuracy and less time to complete real-time recommendation.

关 键 词：协同过滤 推荐系统 聚类 萤火虫算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]