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Using Key Users of Social Networks to Solve Cold Start Problem in Collaborative Recommendation Systems

机译:使用社交网络的关键用户解决协作推荐系统中的冷启动问题

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With the application of collaborative filtering technologies and social network in personalized recommendation system, collaborative recommendation techniques based on social network are now made possible. This paper incorporates key users of social network into the traditional collaborative filtering algorithms to solve cold start problem. Also the influence of key users on recommendation accuracy is verified by experiments. Experimental results show that the key users can improve the accuracy of collaborative filtering algorithm which suggests that the key users can be used to alleviate the impact of cold start problem on the recommendation algorithm.
机译:随着协作过滤技术和社交网络在个性化推荐系统中的应用,基于社交网络的协作推荐技术现在成为可能。本文将社交网络的关键用户纳入传统的协作过滤算法中,以解决冷启动问题。实验还验证了关键用户对推荐准确性的影响。实验结果表明,关键用户可以提高协同过滤算法的准确性,这表明关键用户可以缓解冷启动问题对推荐算法的影响。

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