计算机工程与应用2018，Vol.54Issue(8)：214-219,241,7.DOI:10.3778/j.issn.1002-8331.1609-0445
基于用户相似度和信任度的药品推荐算法
Medicine recommendation algorithm based on user similarity and trust
摘要
Abstract
Aiming at the problem of lower recommendation precision of collaborative filtering, medicine recommenda-tion algorithm based on user similarity and trust is proposed.The method clusters drugs into several groups by using DBSCAN algorithm offline to reduce the time complexity.For the sake of computing the user similarity more precisely, co-rated drugs threshold is introduced to build similar neighbor set of target user,at the same time similarity threshold is introduced to restrict the selection of similar neighbors, which overcomes the defects of KNN algorithm.Then the trust computing model is designed according to recommendation credibility and score reliability.The trustworthy neighbor set of target user is selected in accordance with the degree of trust between users.Finally,drugs are recommended to target user through twice neighbor selection strategy.Experimental results show that compared with the existing algorithms,the proposed algorithm has better performance in mean absolute error,precision and recall ratio,which improves the recom-mendation precision.关键词
协同过滤/信任计算模型/用户相似度/药品推荐Key words
collaborative filtering/trust computing model/user similarity/medicine recommendation分类
信息技术与安全科学引用本文复制引用
肖晓丽,周锡玲..基于用户相似度和信任度的药品推荐算法[J].计算机工程与应用,2018,54(8):214-219,241,7.基金项目
国家自然科学基金(No.61303043) （No.61303043）
湖南省自然科学基金(No.13JJ4052). （No.13JJ4052）
