data sparseness

基本解释

Data sparseness is a serious problem in collaborative filtering system.
数据稀疏性是协同过滤系统面临的一个巨大挑战。
Using pseudowords we can overcome data sparseness problem in supervised WSD and fully verify the experimental effect of word sense classifier.
使用伪词可以避免有指导的词义消歧方法中的数据稀疏问题，充分验证词义分类器的实验效果。
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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。

数据稀疏
This strategy can reduce the data sparseness and keep the search efficiency meanwhile.
这种优化策略可以在保证该算法数据查找效率不变的同时,进一步减少数据稀疏,提高空间利用率。