概念相似度是计算机自然语言处理研究的重要问题之一。
The concept similarity is one of the most important problems in the machine language research.
句子相似度计算在中文自然语言处理领域有着非常广泛的应用背景。
Sentence similarity computing has been widely used in the field of natural language processing.
目前的数学理论和计算实践显示，自然语言处理所需要的时间随输入信息的复杂度呈指数增长。
The current mathematic theory and calculation practices indicate that the time needed to process language information increases with the complexity of the input information exponentially.
句子间相似度的计算在自然语言处理的各个领域都占有很重要的地位，在多文档自动文摘技术中，句子间相似度的计算是一个关键的问题。
Sentence similarity computation is very important in all the fields of Natural Language Processing. In Multi-document Summarization Technology, sentence similarity computation is a key problem.
例如，你可以写关于在自然语言处理中使用机器学习的报告或机器学习中各算法的抽样复杂度的比较整理。
For example, you may write about the use of machine learning in natural language processing or review sample complexity of machine learning algorithms.
我们的研究结果表明，使用自然语料对语言测试效度的影响对不同的考生子团体而言效果有所不同，但总体来看，无助于提高测试效度。
The results of our research show that using original material to different examinee groups can make different effect on test validity, but it's useless to improve the test validity.
我们的研究结果表明，使用自然语料对语言测试效度的影响对不同的考生子团体而言效果有所不同，但总体来看，无助于提高测试效度。
The results of our research show that using original material to different examinee groups can make different effect on test validity, but it's useless to improve the test validity.
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