Representation of rules for relevant recommendations to online social networks users

Sarah Bouraga, Ivan Jureta, Stéphane Faulkner
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引用次数: 2

Abstract

In our prior work, we identified rules for use in recommendation algorithms on Online Social Network (OSN) in order to increase the relevance of content suggested to a user. The resulting recommendation algorithms filter out and prioritize event types for OSN users (such as photo posts by friends, status posts, shared content, etc.), and are thereby intended to reduce information overload. This paper proposes a representation of these rules in a requirements model of a OSN. This is interesting, because recommendation rules influence user behavior, which in turn influences future requirements. If there is a recommendation algorithm, then its behavior should be represented also in requirements models of the system. The paper makes two contributions. We define requirements that OSNs should satisfy in order to produce relevant recommendations of event types to users. We investigate whether an existing requirements modeling language (namely, i-star) can be used to model these requirements.
为在线社交网络用户提供相关建议的规则表示
在我们之前的工作中,我们确定了用于在线社交网络(OSN)推荐算法的规则,以增加向用户推荐的内容的相关性。推荐算法对OSN用户的事件类型(如好友发布的照片、状态、共享内容等)进行过滤和优先级排序,从而减少信息过载。本文提出了这些规则在OSN需求模型中的表示。这很有趣,因为推荐规则会影响用户行为,而用户行为又会影响未来的需求。如果存在推荐算法,那么它的行为也应该在系统的需求模型中表示。这篇论文有两个贡献。我们定义了osn应该满足的需求,以便向用户提供相关的事件类型建议。我们研究是否可以使用现有的需求建模语言(即i-star)来建模这些需求。
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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