Content development using N-gram model in custom writing style

J. Dhar, Vipul Gandhi
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引用次数: 0

Abstract

Amateur writers usually find it difficult and often make errors while building up content when they are doing so in a style different from their own writing style. This causes loss of interest by the readers and sometimes even misinterpretations of actual thoughts desired to be conveyed by author. This work attempts to embark upon this problem statement by ranking the best available choices of words fitting the style of writing that the author would like to adopt. Our methodology allows authors to choose from amongst default, formal and literature style of writing. Also, authors can infer words and traces from his own past writings by developing a custom corpus of his own write-ups. A spell checker and N-gram based statistical model along with a corpus based technique is proposed to achieve above objectives. Rank 4 N-gram along with backoff smoothing provided optimum results for our work. To showcase the effectiveness of this method, we have tested it on real time data and performance evaluation fetched satisfactory results.
使用自定义写作风格的N-gram模型进行内容开发
业余作家通常会发现,当他们用一种与自己写作风格不同的风格来构建内容时,这很难,而且经常会犯错误。这会导致读者失去兴趣,有时甚至会误解作者想要传达的实际思想。这项工作试图通过对适合作者想要采用的写作风格的最佳可用选择的单词进行排名来开始这个问题陈述。我们的方法允许作者从默认,正式和文学写作风格中进行选择。此外,作者可以通过开发自己的文章的自定义语料库,从自己过去的作品中推断出单词和痕迹。为了实现上述目标,本文提出了一个基于拼写检查器和n图的统计模型以及基于语料库的技术。Rank 4 N-gram和backoff平滑为我们的工作提供了最佳结果。为了证明该方法的有效性,我们在实时数据上进行了测试,性能评估取得了满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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