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

机译:使用社交网络解决一类协同过滤中的数据稀疏性问题

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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:一类协作过滤(OCCF)问题比传统协作过滤问题更具问题性,因为OCCF数据集缺少反例。社交网络可用于补救OCCF应用程序面临的数据集问题。在这项工作中,就它们在OCCF问题中的可用性而言,我们比较了属于特定域的社交网络和属于更通用域的社交网络。我们的实验表明,属于特定域的社交网络可能更适合在OCCF应用程序中使用。

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