计算机科学 ›› 2015, Vol. 42 ›› Issue (5): 225-229.doi: 10.11896/j.issn.1002-137X.2015.05.045
王 龙,王嘉伦,程转丽,李 然,张 引
WANG Long, WANG Jia-lun, CHENG Zhuan-li, LI Ran and ZHANG Yin
摘要： 在当前网购越来越流行的趋势下,网上买药也给很多病人带来了极大的便利。但是普通人在网上购买药品时普遍存在盲目购药、无法获得买药指导的问题,针对这一问题,提出首先根据药品的功能描述信息进行聚类,设计了基于用户相似度的协同过滤药品推荐算法；然后针对该算法的冷启动以及数据稀疏性等问题提出了基于张量分解的个性化药品推荐算法来对获取到的药品功能描述信息进行特征分析,构建标签特征向量,利用特征向量与用户对药品的评分值构建三阶张量,再利用张量分解方法对该三阶张量进行分解；最后得到推荐评估值,再利用该推荐评估值进行Top-N药品推荐。通过对真实的药品销售网站数据进行抓取并分析,构建了张量模型,并进行数据建模,与协同过滤的推荐结果相比,其得到了较好的推荐效果。
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