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Autocorrect in Windows 10, correcting the word "mispelled" to "misspelled".. Autocorrection, also known as text replacement, replace-as-you-type, text expander or simply autocorrect, is an automatic data validation function commonly found in word processors and text editing interfaces for smartphones and tablet computers.
Examples include typographical corrections, corrections of minor formatting errors, and reversion of obvious vandalism. A minor edit requires no review and could never be the subject of a dispute. An edit of this kind is marked in its page's revision history with a lowercase, bolded "m" character (m).
Put text in correct font wc/ww: word choice/wrong word: Incorrect or awkward word choice hr # Insert hair space: s/b: should be: Selection should be whatever edit follows this mark s/r: substitute/replace: Make the substitution tr: transpose: Transpose the two words selected vf: verb form (Mostly used when translating) The version of the verb ...
Use complete words, not abbreviations. For example, "Reverting [vandalism]". Preview the page, or review the changes. Publish changes by clicking the Publish changes button. In the page history, your revision will automatically be tagged with (Tag: Manual revert). Some MediaWiki extensions also pop up a text box saying " The page has been ...
1.Compose an email message. 2. Click the Spell check icon. 3. Click on each highlighted word to review spell check suggestions.
[a] The typical way to effect a reversion is to use the "undo" button on the article's history page, but it isn't any less of a reversion if one simply types in the previous text. A single edit may reverse multiple prior edits, in which case the edit constitutes multiple reversions.
AutoComplete is a feature that enables the browser to remember what you enter in a webpage or the browser's address bar. As you’re typing an address, AutoComplete will suggest possible matches.
Edit distance finds applications in computational biology and natural language processing, e.g. the correction of spelling mistakes or OCR errors, and approximate string matching, where the objective is to find matches for short strings in many longer texts, in situations where a small number of differences is to be expected.