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  2. Help:How to write a readable article - Wikipedia

    en.wikipedia.org/wiki/Help:How_to_write_a...

    It should not assume that the reader is well acquainted with the subject of the article. The lead of an article titled "Derivative" should tell a general reader: the field of study of the topic – calculus; the place the topic holds in its field of study – an important tool for mathematical analysis and other fields of study

  3. Help:Your first article - Wikipedia

    en.wikipedia.org/wiki/Help:Your_first_article

    The topic of the article must be notable: it must have in-depth coverage in reliable sources that are independent of the topic. If you are connected to the topic, don't write about it. Find another topic instead. Make sure there isn't already an article about the topic. The article you write must include citations to the sources you used.

  4. Wikipedia:Article wizard - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Article_wizard

    Before creating a draft article, you can practice by first editing in Wikipedia's community sandbox your personal sandbox. It's a great way to try out editing without affecting live articles. If you need some help along the way, see our guide to your first article

  5. Help:Introduction to editing with Wiki Markup/All - Wikipedia

    en.wikipedia.org/wiki/Help:Introduction_to...

    It is best to avoid writing articles about yourself, your company, or someone you know personally. This is because it is difficult to avoid bias and achieve a neutral point of view on these topics. Even if you cannot write the article yourself, you can always request that someone else write it and provide them with reliable sources to use.

  6. Wikipedia:WikiProject Short descriptions - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:WikiProject...

    As the short description is article content, any bot or template generated short description may be overridden with a better short description by an editor. If there is a dispute about whether the new description is better, discuss on the article's talk page.

  7. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    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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