Aiming at the problem of data sparsity for collaborative filtering, a novel rough set-based collaborative filtering algorithm is proposed.
针对协同过滤中的数据稀疏问题，提出了一种基于粗集的协同过滤算法。
The experiment results suggested that IAPCF could provide better recommendation results than the traditional item-based collaborative filtering algorithms.
实验结果表明，IAPCF算法比传统的基于项目的协同过滤算法具有更好的推荐精度。
The result of mining shows that, in the case of the data extremely sparseness, project-based collaborative filtering recommendation method is effective to improve the recommended quality.
挖掘结果表明，在数据极端稀疏的情况下，基于项目的协同过滤推荐方法明显的提高了推荐质量。
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