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  2. Word count - Wikipedia

    en.wikipedia.org/wiki/Word_count

    Word count is commonly used by translators to determine the price of a translation job. Word counts may also be used to calculate measures of readability and to measure typing and reading speeds (usually in words per minute). When converting character counts to words, a measure of 5 or 6 characters to a word is generally used for English. [1]

  3. Google Docs - Wikipedia

    en.wikipedia.org/wiki/Google_Docs

    Google Docs is an online word processor and part of the free, web-based Google Docs Editors suite offered by Google. Google Docs is accessible via a web browser as a web-based application and is also available as a mobile app on Android and iOS and as a desktop application on Google's ChromeOS .

  4. This wiki template is to ease the use of text counting within Word Association Game. {{Wikipedia:Department of Fun/Word Count}} produces the following text: Word count is / as of word: . The parameters must be set, otherwise it produces a dull text.

  5. Automated essay scoring - Wikipedia

    en.wikipedia.org/wiki/Automated_essay_scoring

    Automated essay scoring (AES) is the use of specialized computer programs to assign grades to essays written in an educational setting. It is a form of educational assessment and an application of natural language processing. Its objective is to classify a large set of textual entities into a small number of discrete categories, corresponding ...

  6. Google Docs Editors - Wikipedia

    en.wikipedia.org/wiki/Google_Docs_Editors

    Microsoft Office is a paid suite of productivity apps while Google Docs Editors Suite is available for free to users with private Google accounts. It is also offered as part of Google's business-oriented Google Workspace service, which ran until October 2020 under the name G Suite, a monthly subscription service that unlocks additional features.

  7. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The word with embeddings most similar to the topic vector might be assigned as the topic's title, whereas far away word embeddings may be considered unrelated. As opposed to other topic models such as LDA , top2vec provides canonical ‘distance’ metrics between two topics, or between a topic and another embeddings (word, document, or otherwise).

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