The term "paraphrasing" refers to the process of presenting the sense of an input text in a new way while preserving fluency. Scientific research distribution is gaining traction, allowing both rookie and experienced scientists to participate in their respective fields. As a result, there is now a massive demand for paraphrase tools that may efficiently and effectively assist scientists in modifying statements in order to avoid plagiarism. Natural Language Processing (NLP) is very much important in the realm of the process of document paraphrasing. We analyze and discuss existing studies on paraphrasing in the English language in this paper. Finally, we develop an algorithm to paraphrase any text document or paragraphs using WordNet and Natural Language Tool Kit (NLTK) and maintain "Using Synonyms" techniques to achieve our result. For 250 paragraphs, our algorithm achieved a paraphrase accuracy of 94.8%
翻译：“参数”一词是指以新的方式展示输入文本感的过程,同时保持流畅。科学研究分布正在获得牵引,让新手和有经验的科学家都能够参与各自领域的研究。因此,现在对可高效和有效地协助科学家修改语句的参数性工具的需求很大,可以有效地帮助科学家修改语句,以避免重复。自然语言处理(NLP)在文件参数化过程中非常重要。我们分析和讨论关于本文件中英文的参数化的现有研究。最后,我们开发了一种算法,用WordNet和自然语言工具工具包(NLTK)解释任何文本文件或段落,并维持“使用同地名”技术,以实现我们的结果。对于250段,我们的算法实现了94.8%的参数性精确度。
相关内容
微信扫码咨询专知VIP会员