Improving collaborative filtering with multimedia indexing techniques to create user-adapting Web sites

Arnd Kohrs, B. Mérialdo
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引用次数: 32

Abstract

The Internet is evolving from a static collection of hypertext, to a rich assortment of dynamic services and products targeted at millions of Internet users. For most sites it is a crucial matter to keep a close tie between the users and the site. More and more Web sites build close relationships with their users by adapting to their needs and therefore providing a personal experience. One aspect of personalization is the recommendation and presentation of information and products so that users can access the site more efficiently. However, powerful filtering technology is required in order to identify relevant items for each user. In this paper we describe how collaborative filtering and content-based filtering can be combined to provide better performance for filtering information. Filtering techniques of various nature are integrated in a weighed mix to achieve more robust results and to profit from automatic multimedia indexing technologies. The combined approach is evaluated in a prototype user-adapting Web site, the Active WebMuseum.
使用多媒体索引技术改进协同过滤,以创建适合用户的Web站点
互联网正在从一个静态的超文本集合,发展成为一个针对数百万互联网用户的丰富的动态服务和产品组合。对于大多数网站来说,保持用户和网站之间的紧密联系是至关重要的。越来越多的网站通过适应用户的需求与用户建立密切的关系,从而提供个性化的体验。个性化的一个方面是信息和产品的推荐和呈现,以便用户可以更有效地访问站点。然而,为了识别每个用户的相关项目,需要强大的过滤技术。在本文中,我们描述了如何将协同过滤和基于内容的过滤结合起来,以提供更好的信息过滤性能。各种性质的过滤技术被集成在一个加权组合中,以获得更可靠的结果,并从自动多媒体索引技术中获益。在一个原型用户适应网站Active WebMuseum中对这种组合方法进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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