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Turkish meaningful text generation with class based n-gram model

机译:使用基于类的n-gram模型生成土耳其语有意义的文本

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Text generation systems provide facilities such as making new information deductions from the existing ones, getting information related to them by going out to a knowledgeable way, and generating more detailed results about the calls to the users by generating the codes entered on the internet. In this study, it is aimed to generate meaningful new Turkish sentences using class-based n-gram model from the sentences in the source data set. In order to realize sentence production, a trigram model is proposed and sentences are generated from the word or word groups in the sentence to the number of groups related to it. Thus, new sentences are generated, none of which were identical to the others.
机译:文本生成系统提供了一些功能,例如从现有的信息中推断出新的信息,通过以一种知识渊博的方式获取与之相关的信息,以及通过生成在互联网上输入的代码来生成有关呼叫用户的更详细的结果。在这项研究中,其目的是使用基于类的n-gram模型从源数据集中的句子中生成有意义的新土耳其语句子。为了实现句子的产生,提出了一种三字母组模型,并且根据句子中的单词或单词组到与其相关的组数来生成句子。因此,产生了新句子,没有一个与其他句子相同。

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