data sparseness

基本解釋

Data sparseness is a serious problem in collaborative filtering system.
數(shù)據(jù)稀疏性是協(xié)同過濾系統(tǒng)面臨的一個(gè)巨大挑戰(zhàn)。
Using pseudowords we can overcome data sparseness problem in supervised WSD and fully verify the experimental effect of word sense classifier.
使用偽詞可以避免有指導(dǎo)的詞義消歧方法中的數(shù)據(jù)稀疏問題，充分驗(yàn)證詞義分類器的實(shí)驗(yàn)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.
挖掘結(jié)果表明，在數(shù)據(jù)極端稀疏的情況下，基于項(xiàng)目的協(xié)同過濾推薦方法明顯的提高了推薦質(zhì)量。

數(shù)據(jù)稀疏
This strategy can reduce the data sparseness and keep the search efficiency meanwhile.
這種優(yōu)化策略可以在保證該算法數(shù)據(jù)查找效率不變的同時(shí),進(jìn)一步減少數(shù)據(jù)稀疏,提高空間利用率。