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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.
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.
This usage (section-specific, and tagged for brevity), which is also provided by the shortcut template {{Summary too long}}, will categorize the articles in Category:Articles containing overly long summaries, a hidden cleanup category; to suppress this categorization, use |nocat=y.
It can generate summaries, explanations, and answers based on content uploaded by users. It also includes "Audio Overviews," which summarize documents in a conversational, podcast-like format. [ 1 ] [ 2 ] The team building the product includes popular science author Steven Johnson and product manager Raiza Martin.
If you see something you'd like to change while viewing the summary of your data, many products have a link on the top-right of the page to take you to that product. When you click the product "Your Account," for example, you can click Edit Account Info at the top of the page to access your account settings.
{{Summarize section}} – For sections that are too detailed and need to be summarized. {{ Example farm }} – For excessive use of examples. {{ Too many see alsos }} – For an indiscriminate "See also" section, most of which should be pruned or integrated into the prose.
Wikipedia's scope includes all human knowledge, so we have articles about topics as diverse as science, local history, and popular culture. Volunteers write Wikipedia articles as summaries of the best information on a topic, by summarizing the information found in reliable publications.
Here is an example Summary (including explanations of the Template:Information parameters) that you can copy and paste when you upload the file or refer to when you edit any file Summary that needs correction: