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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.
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.
Paraphrase may apply to music as well as to writing. It was commonplace for Baroque, Classical and Romantic composers to create variations on each other's work without permission. This would not be allowed today. [14]
If a Wikipedia article is constructed through summarizing reliable sources, but there is a paragraph or a few sentences copied from compatibly licensed or public-domain text which is not placed within quotations, then putting an attribution template in a footnote at the end of the sentences or paragraph is sufficient.
INCITE: Cite your sources in the form of an inline citation after the phrase, sentence, or paragraph in question. INTEXT: Add in-text attribution whenever you copy or closely paraphrase a source's words. INTEGRITY: Maintain text–source integrity by placing inline citations in a way that makes clear which source supports which part of the text.
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 quotation or quote is the repetition of a sentence, phrase, or passage from speech or text that someone has said or written. [1] In oral speech, it is the representation of an utterance (i.e. of something that a speaker actually said) that is introduced by a quotative marker, such as a verb of saying.
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.
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