| 摘 要: 推荐系统是互联网和电子商务的产物。它是建立在对海量数据训练的基础上的一种智能平台，能够向 顾客提供个性化的信息服务和决策。随着电子商务大数据的高速发展，推荐系统正逐渐成为学术界的研究热点之一。 针对推荐系统理论性强、内容抽象的特点，本文介绍了以MyMediaLite为平台的个性化推荐实践方案，并详细阐述了 其具体的实施过程。通过介绍MyMediaLite的系统结构框架，以及分析基于MyMediaLite的实验过程，为研究者使用 MyMediaLite推荐系统库进行算法研究奠定了基础。 |
| 关键词: 个性化推荐；机器学习；MyMediaLite；推荐系统；协同过滤 |
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中图分类号: TP317
文献标识码: A
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| 基金项目: 南京审计大学大学生创新创业训练计划资助(编号：2016AX04001Z). |
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| Research on the Recommendation Method Based on the MyMediaLite Platform |
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LIN Nan,YANG Wenyuan,MA Yili,ZHU Tingting,CHENG Shenglei
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( School of Economics and Trade, Nanjing Audit University, Nanjing 211815, China)
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| Abstract: The recommendation system is the product of Internet and e-commerce.It is an intelligent platform built on the basis of massive data training.It provides personalized information service and decision-making to customers. With the rapid development of big data in electronic commerce,the recommendation system is becoming one of the hot topics in the academic field.In view of the highly theoretical and abstract nature of the recommendation system,this paper introduces the personalized recommending practice scheme based on MyMediaLite,and expounds its specific implementation process in detail.By introducing the system framework of MyMediaLite and analyzing the experimental process based on MyMediaLite,it establishes a foundation for researchers to conduct studies on the algorithms with MyMediaLite recommendation system library. |
| Keywords: personalized recommendation;machine learning;Mymedialite;the recommendation system;collaborative filtering |
