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  2. Help:Searching/Features - Wikipedia

    en.wikipedia.org/wiki/Help:Searching/Features

    A comma separated list of the fields to use. Allowed fields are title, text, auxiliary_text, opening_text, headings and all. &cirrusMltUseFields (true or false) use only the field data. Defaults to false: the system will extract the content of the text field to build the query. &cirrusMltPercentTermsToMatch: The percentage of terms to match on.

  3. Lesk algorithm - Wikipedia

    en.wikipedia.org/wiki/Lesk_algorithm

    The Lesk algorithm is based on the assumption that words in a given "neighborhood" (section of text) will tend to share a common topic. A simplified version of the Lesk algorithm is to compare the dictionary definition of an ambiguous word with the terms contained in its neighborhood. Versions have been adapted to use WordNet. [2]

  4. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus.

  5. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  6. Stemming - Wikipedia

    en.wikipedia.org/wiki/Stemming

    In linguistic morphology and information retrieval, stemming is the process of reducing inflected (or sometimes derived) words to their word stem, base or root form—generally a written word form. The stem need not be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this ...

  7. Bag-of-words model - Wikipedia

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

    The bag-of-words model (BoW) is a model of text which uses a representation of text that is based on an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity.

  8. Today's Wordle Hint, Answer for #1257 on Wednesday, November ...

    www.aol.com/todays-wordle-hint-answer-1257...

    Related: 16 Games Like Wordle To Give You Your Word Game Fix More Than Once Every 24 Hours We'll have the answer below this friendly reminder of how to play the game .

  9. WordNet - Wikipedia

    en.wikipedia.org/wiki/WordNet

    WordNet aims to cover most everyday words and does not include much domain-specific terminology. WordNet is the most commonly used computational lexicon of English for word-sense disambiguation (WSD), a task aimed at assigning the context-appropriate meanings (i.e. synset members) to words in a text. [14]