x -hint:一个实现面向社会的推荐系统的框架

A. Panisson, G. Ruffo, R. Schifanella
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引用次数: 1

摘要

根据产生信息过载的数据驱动应用程序的本质,用户需要一个支持来做出选择,即使没有足够的替代方案的个人经验。在这种情况下,社会网络技术可以用于寻找用户之间的亲和力,并以个性化的方式过滤信息。在提出了社交推荐系统的通用模型(称为X-Hinter)之后,我们描述了一个Java API,该API提供了一组库和工具,用于在广泛的领域中构建社交过滤系统。一个名为DeHinter的原型实现显示了所提出的方法在P2P文件共享应用程序中的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
X-hinter: a framework for implementing social oriented recommender systems
Accordingly to the nature of data-driven applications that produce information overload, users need a support to make choices, even without sufficient personal experience of the alternatives. In this context, social networking techniques could be useful applied for finding affinities between users and filter information in a personalized way. After proposing a generalized model for social recommender systems, called X-Hinter, we describe a Java API that provides a set of libraries and tools to build social filtering systems in a wide range of domains. A prototype implementation, named DeHinter, shows the feasibility of the proposed approach in a P2P file sharing application.
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