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2. LanguageTool - Wikipedia

   en.wikipedia.org/wiki/LanguageTool

   The core app itself is free and open-source and can be downloaded for offline use. Some languages use ' n-gram ' data, [ 7 ] which is massive and requires considerable processing power and I/O speed, for some extra detections.

3. Grammar checker - Wikipedia

   en.wikipedia.org/wiki/Grammar_checker

   The fact that a natural word may be used as any one of several parts of speech (such as "free" being used as an adjective, adverb, noun, or verb) greatly increases the complexity of any grammar checker. A grammar checker will find each sentence in a text, look up each word in the dictionary, and then attempt to parse the sentence into a form ...

4. Grammarly - Wikipedia

   en.wikipedia.org/wiki/Grammarly

   Documents whose contents have been corrected via Grammarly have occasionally been accused by detection engines such as Turnitin of being partially or entirely AI-generated. [39] Schools are struggling to develop rules about its use that are consistent and fair, with some teachers recommending Grammarly to all of their students and others ...

5. Reverso (language tools) - Wikipedia

   en.wikipedia.org/wiki/Reverso_(language_tools)

   [12] [13] These texts are sourced mainly from films, books, and governmental documents, allowing users to see idiomatic usages of translations as well as synonyms and voice output. The Reverso Context app also provides language-learning features such as flashcards based on words in example sentences. [14]

6. English grammar - Wikipedia

   en.wikipedia.org/wiki/English_grammar

   The first published English grammar was a Pamphlet for Grammar of 1586, written by William Bullokar with the stated goal of demonstrating that English was just as rule-based as Latin. Bullokar's grammar was faithfully modeled on William Lily's Latin grammar, Rudimenta Grammatices (1534), used in English schools at that time, having been ...

7. Bag-of-words model - Wikipedia

   en.wikipedia.org/wiki/Bag-of-words_model

   It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a classifier. [1] It has also been used for computer vision. [2]