计算机应用研究2017，Vol.34Issue(12)：3585-3588,4.DOI:10.3969/j.issn.1001-3695.2017.12.015
基于Spark的混合推荐算法研究
Research on hybrid recommendation algorithm based on Spark technology
摘要
Abstract
Due to the development of e-commerce,traditional stand-alone model is difficult to meet the needs of massive data in real-time recommendation.And collaborative filtering-based recommender system has become increasingly evident.Therefore,this paper proposed a distributed recommendation method based on Spark computing model,which the theory was based on spectral clustering and Naive Bayes.In addition,the hybrid method used the increment update schemes to refresh the ratings and improved the precision of the system,without all the re-training model.The experimental results demonstrate that to be compared with traditional stand-alone mode recommendation algorithm,the distributed recommendation algorithm overcomes sparsity and scalability problem to a certain extent and has higher scalability and reduces the response time of the system.关键词
推荐算法/分布式计算/Spark/增量式更新Key words
recommendation algorithm/distributed computation/Spark/incremental update分类
信息技术与安全科学引用本文复制引用
胡德敏,龚燕..基于Spark的混合推荐算法研究[J].计算机应用研究,2017,34(12):3585-3588,4.基金项目
国家自然科学基金资助项目(61170277,61472256) （61170277,61472256）
上海市教委科研创新重点资助项目(12zz137) （12zz137）
上海市一流学科建设资助项目(S1201YLXK) （S1201YLXK）
