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  2. Text corpus - Wikipedia

    en.wikipedia.org/wiki/Text_corpus

    Machine translation algorithms for translating between two languages are often trained using parallel fragments comprising a first-language corpus and a second-language corpus, which is an element-for-element translation of the first-language corpus. [3] Philologies. Text corpora are also used in the study of historical documents, for example ...

  3. List of text corpora - Wikipedia

    en.wikipedia.org/wiki/List_of_text_corpora

    Text corpora (singular: text corpus) are large and structured sets of texts, which have been systematically collected.Text corpora are used by both AI developers to train large language models and corpus linguists and within other branches of linguistics for statistical analysis, hypothesis testing, finding patterns of language use, investigating language change and variation, and teaching ...

  4. Word n-gram language model - Wikipedia

    en.wikipedia.org/wiki/Word_n-gram_language_model

    To prevent a zero probability being assigned to unseen words, each word's probability is slightly lower than its frequency count in a corpus. To calculate it, various methods were used, from simple "add-one" smoothing (assign a count of 1 to unseen n -grams, as an uninformative prior ) to more sophisticated models, such as Good–Turing ...

  5. Corpus linguistics - Wikipedia

    en.wikipedia.org/wiki/Corpus_linguistics

    Corpus linguistics is an empirical method for the study of language by way of a text corpus (plural corpora). [1] Corpora are balanced, often stratified collections of authentic, "real world", text of speech or writing that aim to represent a given linguistic variety. [1] Today, corpora are generally machine-readable data collections.

  6. 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]

  7. Google Books Ngram Viewer - Wikipedia

    en.wikipedia.org/wiki/Google_Books_Ngram_Viewer

    The program can search for a word or a phrase, including misspellings or gibberish. [5] The n-grams are matched with the text within the selected corpus, and if found in 40 or more books, are then displayed as a graph. [6] The Google Books Ngram Viewer supports searches for parts of speech and wildcards. [6] It is routinely used in research. [7 ...

  8. Word list - Wikipedia

    en.wikipedia.org/wiki/Word_list

    Some major pitfalls are the corpus content, the corpus register, and the definition of "word". While word counting is a thousand years old, with still gigantic analysis done by hand in the mid-20th century, natural language electronic processing of large corpora such as movie subtitles (SUBTLEX megastudy) has accelerated the research field.

  9. Treebank - Wikipedia

    en.wikipedia.org/wiki/Treebank

    Treebanks are necessarily constructed according to a particular grammar. The same grammar may be implemented by different file formats. For example, the syntactic analysis for John loves Mary, shown in the figure on the right/above, may be represented by simple labelled brackets in a text file, like this (following the Penn Treebank notation):