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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.
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.
Users can use the tool to paraphrase text being composed on services like Gmail, Google Docs, Facebook, Twitter, and LinkedIn. [ 10 ] On November 14, 2021, AI21 released Wordtune Read — an AI-powered Chrome extension and standalone app designed to process large amounts of written text from websites, documents, or YouTube videos, and summarize ...
The evaluation of paraphrase generation has similar difficulties as the evaluation of machine translation. The quality of a paraphrase depends on its context, whether it is being used as a summary, and how it is generated, among other factors. Additionally, a good paraphrase usually is lexically dissimilar from its source phrase.
Reading comprehension and vocabulary are inextricably linked together. The ability to decode or identify and pronounce words is self-evidently important, but knowing what the words mean has a major and direct effect on knowing what any specific passage means while skimming a reading material.
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.
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