基于混合推荐的智能导赏服务设计

Ki-Sook Chung, T. Tung, ChangSup Keum
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引用次数: 1

摘要

亚马逊和Netflix等电子商务公司一直在引入推荐技术来吸引他们的网站客户。在亚马逊(Amazon.com),他们使用推荐算法为每位客户定制个性化的在线商店。许多应用程序收集客户的兴趣来生成一个推荐项目列表。我们将推荐算法引入到智能导赏服务中,根据游客的偏好和其他条件(如他在博物馆或美术馆的位置)来引导游客。我们使用了一种混合的方法,结合了项目-项目协同过滤和人口统计推荐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A design of smart docent service using hybrid recommenders
E-commerce companies such as Amazon.com and Netflix have been introducing recommendation techniques to attract their customers on their web sites. At Amazon.com, they use recommendation algorithms to personalize the online store for each customer. Many applications collect customer's interests to generate a list of recommended items. We introduce recommendation algorithms to smart docent service which guides the visitor considering his preference and other conditions such as his location in museums or art galleries. We use a hybrid approach which combines item-item collaborative filtering and demographical recommendation.
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