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。

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To efficiently resolve the problem that the new item is difficult to recommend in collaborative filtering algorithm. In this paper we propose a new method based item matrix partition.

为了有效地解决协同过滤算法中新项目难以推荐的问题，文中提出了一种对项目矩阵进行划分的方法。

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A collaborative filtering recommendation algorithm based on the item features model is proposed in this paper.

提出一种基于项目特征模型的协同过滤推荐算法。

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