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。
Using pseudowords we can overcome data sparseness problem in supervised WSD and fully verify the experimental effect of word sense classifier.
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。
Aiming at the problem of data sparsity for collaborative filtering, a novel rough set-based collaborative filtering algorithm is proposed.
现有平滑技术利用不同的折扣和补偿策略来处理数据稀疏问题，在计算复杂性与合理性方面各有其优缺点。
The present smoothing techniques deal with the data sparse problem using different discount and compensate strategy, and they have different merit or shortcoming on complexity and rationality.
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