Contoh sparseness

• This sparseness is actually a factor throughout the book, despite the practical detail in the case studies.

• The sparseness of food resources kept population densities quite low prior to the development of agriculture.

• This is justified by the fact that sparseness is far more severe for lexical probabilities than for language model probabilities.

• This is a typical result of the data sparseness we have encountered while training the word-based model.

• We can overcome the problem of data sparseness by applying not co-occurring words but co-occurring clusters to the similarity of target words.

• When we consider the words with different inflectional and derivational suffixes different, then we have to deal with data sparseness.

• Some influence of temporal sparseness upon the strength of the feedback would be required in that case.

• Thus, one would expect the variance in the estimated responses to grow with increasing sparseness.

• We surmise that these constraints simply differ from corpus to corpus and are related to general data sparseness effects.

• Traditional attempts to tackle the problem of data sparseness include the class-based approaches and similarity-based approaches.

• To do this, we make use of some properties of sparse matrices since nearly all economic models display sparseness.

• Note that, due to data sparseness, all of these words, though related with soccer have less probability when compared to stem-based and noun-based models.

• This sparseness limits the communication necessary through the constraint network, and permits effective distribution of work among agents.

• The girth as another graph parameter controlling the sparseness of a graph is less well studied in this context.

• We should take into consideration the data sparseness problem because the data do not contain all phenomena of the language in most cases.