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A Method of Generating Customer's Profile without History for Providing Recommendation to New Customers in E-Commerce

机译：一种无需历史记录即可生成客户档案的方法，以向电子商务中的新客户提供推荐

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摘要

One of the advantages in E-commerce is that the long tail marketing strategy can be employed. By this, customers can get recommendations about the items, which are rare and specialized to their own tastes. In order to provide this long tail based recommendation service, the service provider needs to have knowledge about the each user's preference and the similarity among the items which have their own peculiar. If the customer's purchasing transaction history is provided, his/her preference can be inferred through data mining techniques. But if a customer is new and the purchasing history is empty, it is hard to extract the collect profile for the customer. In this paper, a method of defining the customer's profile through collective intelligence is proposed. This method can generate profile even if the customer's personal history does not exist. Therefore a proper recommendation can be provided to newcomers in the service.
机译：电子商务的优势之一是可以采用长尾营销策略。通过这种方式，顾客可以获得关于这些产品的推荐，这些推荐是罕见的并且专门针对他们自己的口味。为了提供这种基于长尾的推荐服务，服务提供者需要具有关于每个用户的偏爱以及具有自己独特项的项目之间的相似性的知识。如果提供了客户的购买交易历史记录，则可以通过数据挖掘技术推断出他/她的偏好。但是，如果客户是新客户并且购买历史记录为空，则很难为该客户提取收集配置文件。本文提出了一种通过集体智能定义顾客档案的方法。即使客户的个人历史不存在，此方法也可以生成配置文件。因此，可以向服务中的新手提供适当的建议。

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