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Using Social Networks to Solve Data Sparsity Problem in One-Class Collaborative Filtering

机译:使用社交网络解决单级协同筛选中的数据稀疏问题

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One-Class Collaborative Filtering (OCCF) problems are more problematic than traditional collaborative filtering problems, since OCCF datasets lack counter-examples. Social networks can be used to remedy dataset issues faced by OCCF applications. In this work, we compare social networks belong to specific domains and the ones belong to more generic domains in terms of their usability in OCCF problems. Our experiments show that social networks that belong to a specific domain may better be appropriate for use in OCCF application.
机译:一流的协作过滤(OCCF)问题比传统的协作过滤问题更有问题,因为OCCF数据集缺乏反击示例。社交网络可用于解决OCCF应用程序所面临的数据集问题。在这项工作中,我们比较社交网络属于特定域,而且在他们的可用性中属于更多泛型域。我们的实验表明,属于特定域属于特定域的社交网络可能更适合在OCCF应用中使用。

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