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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.
For avoidance of plagiarism of text copied from compatibly licensed copyleft publications and public domain publications, see also the section below: Copying material from free sources. You can avoid plagiarism by summarizing source material in your own words followed by an inline citation, or by quoting or closely paraphrasing the source ...
Semantic Scholar is a research tool for scientific literature. It is developed at the Allen Institute for AI and was publicly released in November 2015. [2] Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing automatically generated summaries of scholarly papers. [3]
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. In such a way, multi-document summarization systems are complementing the news aggregators performing the next step down the road of coping with ...
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The TV style guideline specifies a maximum of 200 words for entries in episode lists and up to 400 words for standalone episode articles. The Video game style guideline advises no more than approximately 700 words. While longer descriptions may appear to provide more information, a concise summary can highlight the most important plot elements.
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