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English: This is the Teacher's Guide of the "Reading Wikipedia in the Classroom" program corresponding to Module 3 in Spanish. "Reading Wikipedia in the Classroom" is a professional development program for secondary school teachers led by the Education team at the Wikimedia Foundation.
Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts
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.
Here is a summary of the steps to add a new subcategory and a new topic code to the table for Template:Expand Spanish (details follow): determine which missing topic code you wish to add (e.g., 'bio'; see col 1 of the topic table )
The to/from and article title parameters are optional, but it is highly recommend that you fill them out so that people know why the template is there. If the page name you provide in the article title parameter does not exist, the template will display without the article name (it will still make sense, but vaguely suggest only "another article".
{{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.
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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.