Context-based preference analysis method in ubiquitous commerce

J. Hwang, Myung-Jin Lee, O. Kwon, K. Ryu
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引用次数: 4

Abstract

As the age of ubiquitous commerce is upon us, personalization service is getting interested. Therefore, the recommendation methods that offer useful information to the customers become more important. However, most of them depend on a specific method and are restricted to the e-commerce. For applying these recommendation methods into U-commerce, first it is necessary that the extended context modeling and systematic connection of the methods to supplement some deficiency of each recommendation method. Therefore, we propose a modeling technique of context information related to personal activity in commercial transaction and show incremental preference analysis method, using preference tree which is closely connected to recommendation method in each step. And also, we use an XML indexing technique to efficiently extract the recommendation information from a preference tree.
泛在商业中基于上下文的偏好分析方法
随着无处不在的商业时代的到来,个性化服务越来越受到关注。因此,为客户提供有用信息的推荐方法变得更加重要。然而,它们大多依赖于特定的方法,并且仅限于电子商务。为了将这些推荐方法应用到U-commerce中,首先需要对这些方法进行扩展的上下文建模和系统的连接,以补充每种推荐方法的不足。因此,我们提出了一种商业交易中与个人活动相关的上下文信息建模技术,并提出了增量偏好分析方法,在每一步中使用与推荐方法密切相关的偏好树。同时,利用XML索引技术从偏好树中高效地提取推荐信息。
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