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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.
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 ]
Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.
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.
Communication strategies are strategies that learners use to overcome these problems in order to convey their intended meaning. [1] Strategies used may include paraphrasing, substitution, coining new words, switching to the first language, and asking for clarification.
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.