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云计算环境下基于协同过滤的个性化推荐机制 被引量：39

A Collaborative Filtering Recommendation Mechanism for Cloud Computing
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摘要 随着云计算时代的到来,应用数据量剧增,个性化推荐技术日趋重要.然而由于云计算的超大规模以及分布式处理架构等特点,将传统的推荐技术直接应用到云计算环境时会面临推荐精度低、推荐时延长以及网络开销大等问题,导致推荐性能急剧下降.针对上述问题,提出一种云计算环境下基于协同过滤的个性化推荐机制RAC.该机制首先制定分布式评分管理策略,通过定义候选邻居(candidate neighbor,CN)的概念筛选对推荐结果影响较大的项目集,并构建基于分布式存储系统的2个阶段评分索引,保证推荐机制快速准确地定位候选邻居;在此基础上提出基于候选邻居的协同过滤推荐算法(candidate neighbor-based distribited collaborative filtering algorithm,CN-DCFA),在候选邻居中搜索目标用户已评分项目的k近邻,预测目标用户的推荐集top-N.实验结果表明,在云计算环境下RAC拥有良好的推荐精度和推荐效率. The advent of cloud computing has witnessed a sharp augmentation in the amount of application data, the result of which gives more and more prominence to a personalized recommendation technique, which has been used by different kinds of Web applications. However, traditional collaborative filtering （CF） techniques, when applied to cloud computing which features a huge scale and distributed processing architecture, are confronted with some problems, such as low recommendation accuracy, long recommendation time and high network traffic. Consequently, the performance of recommendation mechanisms degrades drastically. To address this issue, a CF recommendation mechanism for cloud computing （RAC） is proposed in this paper. RAC first employs a candidate neighbor, the definition of which will also be given, to screen those items which exert great influence on the recommendation results. Then a 2-stage rating indexing structure based on distributed storage system will be constructed to ensure the quick and precise location of CN by RAC. On this basis, a CN-based CF recommendation algorithm CN-DCFA which searches k nearest neighbors between candidate neighbors can be provided. Meanwhile, CN-DCFA utilizes similarity to predict the recommendation results top-N of active users. Experiments have showed that our recommendation mechanism RAC, enjoying great efficiency and exactitude, is worthy of recommendation.
作者 朱夏 宋爱波 东方 罗军舟
机构地区 东南大学计算机科学与工程学院
出处 《计算机研究与发展》 EI CSCD 北大核心 2014年第10期2255-2269,共15页 Journal of Computer Research and Development
基金 国家"九七三"重点基础研究发展计划基金项目(2010CB328104) 国家自然科学基金项目(61202449 61272054 61370207 61320106007) 国家"八六三"高技术研究发展计划基金项目(2013AA013503) 国家科技支撑计划基金项目(2010BAI88B03 2011BAK21B02) 高等学校博士学科点专项科研基金项目(20110092130002) 江苏省产学研前瞻性联合研究项目(BY2012202) 江苏省科技成果转化专项资金项目(BA2012036) 江苏省网络与信息安全重点实验室资助项目(BM2003201) 计算机网络和信息集成教育部重点实验室资助项目(93K-9)
关键词 协同过滤 个性化推荐 云计算 候选邻居 分布式评分管理 collaborative filtering personalized recommendation cloud computing candidate neighbor distributed rating management
分类号 TP393 [自动化与计算机技术—计算机应用技术]
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参考文献27

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二级参考文献17

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共引文献13

同被引文献334

引证文献39

二级引证文献277

计算机研究与发展
2014年 第10期

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