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A Social Network system oriented hybrid recommendation model

机译:面向社交网络系统的混合推荐模型

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In the framework of Data Vitalization, data has inner connection. In this paper, we apply it to recommendation system of Social Networking Services. With the development of Social Networking Services, the research and application of SNS flourish. In SNS, recommendation for users is a significant feature. Recommending items that will be accepted by users is a key point. Considering the feature of SNS data, traditional recommendation based-on content or based-on collaborative filtering can't be fully applied to SNS. In this paper, we combine recommendation based-on content with that based-on collaborative filtering. And propose the concept of user intimacy based on the interaction between users. With these three aspects, we construct a hybrid recommendation model. Experiment is conduct to show advantage of the model in accuracy and verify its practicality.
机译:在数据活力化框架中,数据具有内在联系。在本文中,我们将其应用于社交网络服务推荐系统。随着社交网络服务的发展,SNS的研究和应用蓬勃发展。在SNS中,对用户的推荐是一项重要功能。推荐用户将接受的项目是关键。考虑到SNS数据的特征,传统的基于内容推荐或基于协作过滤的推荐不能完全应用于SNS。在本文中,我们将基于推荐的内容与基于协同过滤的内容相结合。并提出了基于用户之间互动的用户亲密概念。从这三个方面,我们构建了一个混合推荐模型。通过实验证明了该模型在准确性上的优势,并验证了其实用性。

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