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Analysis of language features of English corpus based on Java Web

机译：基于Java Web的英语语料库语言特征分析

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摘要

Corpus is relative to other similar language has many language users. The impact of this situation on corpus based language research and corpus. In a few cases, the corpus is processed This paper briefly introduces an overview of Corpus processing tools and recently provided free of charge, and examines some of the corpus linguist may prevent the same problem. These questions reveal a new language resources, rich and necessity of corpus-based promotion. Therefore, the introduction of a new Java Web corpus, which includes all modern standards-based design from Corpus varieties include more than two million words of the newspaper, the translation is collected from undergraduate university students, in order to ensure a strong knowledge of the language. Java a parallel corpus of English language feature will help in comparing these languages. By rendering all the packages, which will be set as an initial data packet all prepared for further analysis based on baseline corpus. The obtained results are shown for a better listening when awakened into classes, price than when the corpus is divided into categories. Language Category achieve recognition rate of emotion mixed corpus of 91%. Overall, it's better than language classification; however, when we only use two classes, the performance results are roughly the same.
机译：语料库是相对于其他类似的语言有许多语言的用户。这种情况对基于语料库语言研究和语料库的影响。在一些情况下，Corpus被处理，本文简要介绍了语料库处理工具的概述，最近免费提供，并检查一些语料库语言学家可能会阻止同样的问题。这些问题揭示了基于语料库的新语言资源，丰富和必要性。因此，引入新的Java Web语料库，包括来自语料库品种的所有现代标准的设计包括超过200万字的报纸，从本科大学生中收集了翻译，以确保强烈了解了语。 Java一个平行的英语语言语料库将有助于比较这些语言。通过呈现所有包，将被设置为初始数据包，所有这些数据包都准备用于基于基线语料库的进一步分析。当唤醒课程时，所获得的结果显示出更好的聆听，价格比语料库分为类别。语言类别达到情感混合核肉的识别率为91％。总的来说，它比语言分类更好;但是，当我们只使用两个类时，性能结果大致相同。

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