电子商务中的商品推荐系统

余文喆; 张蓉; 王立

电子商务中的商品推荐系统

1.
华东师范大学软件学院,上海 200062

详细信息

中图分类号: TP31
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- 被引次数: 0
出版历程
- 收稿日期: 2013-03-01
- 修回日期: 2013-04-01
- 刊出日期: 2013-05-25

Recommendation in E-commerce

1.
Software Engineering Institute, East China Normal University, Shanghai 200062, China

摘要

摘要: 对于迅速崛起的各种电子商务网站来说，为了促进网站发展和增加经济效益，吸引新客户并留住老客户是一种有效的手段.设计和实现高效的商品推荐算法是各大网站最为关注的技术之一.在电子商务网站中常见的一种推荐方式是以广告的形式在边栏推荐商品.目前，商品推荐系统根据推荐算法分为基于内容、协同过滤和混合的推荐系统.然而，现有推荐算法在电子商务网站的实际应用中正面临挑战，包括推荐结果的多样化、个性化和智能化以及时效化.现有算法需要不断改进来解决这些问题，从而完善电子商务推荐系统.
- 电子商务 /
- 推荐系统 /
- 多样化 /
- 个性化 /
- 智能化 /
- 时效化
Abstract: For e-commerce sites, in order to promote the development and win more benefits, attracting and keeping the customers becomes very important. One of the most useful technologies is recommendation algorithms. In e-commerce sites, sidebar advertising is a common form of recommendation, which can be divided into three main categories: content-based, collaborative filtering and hybrid recommendation algorithms. However, current recommendation algorithms are challenged by new application requirements, such as diversification, personalization, intelligentization and timeliness. It is urgent to design new algorithms to meet these requirements.
- e-commerce /
- recommendation systems /
- diversification /
- personalization /
- intelligentization /
- timeliness

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参考文献(1)

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