CAJ | 학술논문

　　为了提高商品推荐系统的性能，从理解B2C电子商务平台客户的购物倾向角度出发，进行实时的商品推荐。本文总结归纳了B2C电子商务平台的主要商品推荐位，以及如何基于商品信息建立商品标签，如何判别商品的相似性、相同性。在上述工作的基础上，重点论述了基于客户购物倾向的实时的商品推荐方案。本文对已有工作进行了深入对比和分析，对提出的方案进行了必要的理论分析和性能评估。并从XBRL的技术角度，对商品推荐方案进行了改进。
　　위료제고상품추천계통적성능，종리해B2C전자상무평태객호적구물경향각도출발，진행실시적상품추천。본문총결귀납료B2C전자상무평태적주요상품추천위，이급여하기우상품신식건립상품표첨，여하판별상품적상사성、상동성。재상술공작적기출상，중점논술료기우객호구물경향적실시적상품추천방안。본문대이유공작진행료심입대비화분석，대제출적방안진행료필요적이론분석화성능평고。병종XBRL적기술각도，대상품추천방안진행료개진。
To improve the performance of the commodity recommendation system, this paper proposes two methods:(1) recommend commodity in real-time;(2) understand customers’ purchase intentions. In order to achieve the above goals, we summarize commodity recommendation location, and the label of commodity. Based on the above, we propose a scheme to improve the performance of the commodity recommendation system. We conduct an in-depth analysis on existing work, and give necessary theoretical analysis and performance evaluation for the proposed commodity recommend scheme. From the technical point of view, this method improves the above commodity recommend scheme.