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第五章:电子商务推荐系统
陈震宇
东北大学管理学院
什么是推荐系统?
The Nextflix prize story
In October 2006, Netflix announced it would give a $1 million to whoever created a movie-mending algorithm 10% better than its own.
Within two weeks, the DVD pany had received 169 submissions, including three that were slightly superior to Cinematch, Netflix's mendation software
After a month, more than a thousand programs had been entered, and the top scorers were almost halfway to the goal
But what started out looking simple suddenly got hard. The rate of improvement began to slow. The same three or four teams clogged the top of the leader-board.
The Nextflix prize story
Progress was almost imperceptible, and people began to say a 10 percent improvement might not be possible.
Three years later, on 21st of September 2009, Netflix announced the winner.
电子商务推荐系统概念
Harvard商学院的Joe Ping在大规模定制一文中认为现代企业应该从大规模生产(以标准化的产品和均匀的市场为特征)向大规模定制(为不同客户的不同需求提供不同的商品)转化。
电子商务推荐系统(mendation System)向客户提供商品信息和建议,模拟销售人员帮助客户完成购买过程。
推荐系统在互联网产品与服务推荐中广泛使用.
大多数电子商务网站有推荐系统.
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电子商务推荐系统作用
电子商务推荐系统的两个重要功能.
面对海量信息,推荐系统帮助使用者解决信息过载问题.
推荐系统帮助商家销售更多商品,获取更多利润.
从商家的角度,电子商务推荐系统有助于:
将电子商务网站的浏览者转变为购买者(Converting Browsers into Buyers)
提高电子商务网站的交叉销售能力(Cross-Selling)
提高客户对电子商务网站的忠诚度(Building Loyalty)
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电子商务推荐系统分类
电子商务推荐系统的输出:
建议(Suggestion)
单个建议(Single Item)
未排序建议列表(Unordered List)
排序建议列表(Ordered List)
预言(Prediction):系统对给定项目的总体评分
个体评分(Individual Rating):输出其他客户对商品的个体评分
评论(Review):输出其他客户对商品的文本评价
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