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Paraphrase or paraphrasing in computational linguistics is the natural language processing task of detecting and generating paraphrases. Applications of paraphrasing are varied including information retrieval, question answering , text summarization , and plagiarism detection . [ 1 ]
A paraphrase or rephrase (/ ˈ p ær ə ˌ f r eɪ z /) is the rendering of the same text in different words without losing the meaning of the text itself. [1] More often than not, a paraphrased text can convey its meaning better than the original words. In other words, it is a copy of the text in meaning, but which is different from the original.
In the 1980s, Annemarie Sullivan Palincsar and Ann L. Brown developed a technique called reciprocal teaching that taught students to predict, summarize, clarify, and ask questions for sections of a text. The use of strategies like summarizing after each paragraph has come to be seen as effective for building students' comprehension.
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
This definition is a cornerstone of the taxonomy of educational goals, widely applied beyond education, notably in knowledge management. Knowledge is categorized into specific domains: the recall of terminology and facts, understanding methods and conventions, and recognizing patterns and principles in various fields.
Many direct quotations can be minimized in length by providing an appropriate context in the surrounding text. A summary or paraphrase of a quotation is often better where the original wording could be improved. Consider minimizing the length of a quotation by paraphrasing, by working small portions of the quotation into the article text, or both.