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。
Although the sparseness of the data may suggest that the social network is not always applicable, a solution to utilize the network in these cases is presented.
数据的稀疏性意味着社会网络并不总是可用，在这种情况下提出一种解决方案，很好地利用了社会网络的有效信息。
Such a taxonomy is expected to be particularly useful here, due to the large number of items and the sparseness of data per item (mostly attributed to "tracks" rather than to "artists").
这样的分类是非常有用的，因为条目巨多并且每条数据不全（因为有 "track"属性而没有 "artists" 属性）。
The data sets have features such as high-dimensional, sparseness and binary value in many clustering applications.
在许多聚类应用中，数据对象是具有高维、稀疏、二元的特征。
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。
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。
应用推荐