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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Word2vec is a technique in natural language ... For example, word2vec has been used to map a vector space of words in one language to a vector space constructed from ...

  3. 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]

  4. n-gram - Wikipedia

    en.wikipedia.org/wiki/N-gram

    Figure 1 shows several example sequences and the corresponding 1-gram, 2-gram and 3-gram sequences. Here are further examples; these are word-level 3-grams and 4-grams (and counts of the number of times they appeared) from the Google n-gram corpus. [4] 3-grams ceramics collectables collectibles (55) ceramics collectables fine (130)

  5. Cosine similarity - Wikipedia

    en.wikipedia.org/wiki/Cosine_similarity

    For example, in information retrieval and text mining, each word is assigned a different coordinate and a document is represented by the vector of the numbers of occurrences of each word in the document. Cosine similarity then gives a useful measure of how similar two documents are likely to be, in terms of their subject matter, and ...

  6. Distributional semantics - Wikipedia

    en.wikipedia.org/wiki/Distributional_semantics

    Distributional semantics [1] is a research area that develops and studies theories and methods for quantifying and categorizing semantic similarities between linguistic items based on their distributional properties in large samples of language data.

  7. Today’s NYT ‘Strands’ Hints, Spangram and Answers for ...

    www.aol.com/today-nyt-strands-hints-spangram...

    An example spangram with corresponding theme words: PEAR, FRUIT, BANANA, APPLE, etc. Need a hint? Find non-theme words to get hints. For every 3 non-theme words you find, you earn a hint.

  8. Latent space - Wikipedia

    en.wikipedia.org/wiki/Latent_space

    Word2Vec: [4] Word2Vec is a popular embedding model used in natural language processing (NLP). It learns word embeddings by training a neural network on a large corpus of text. Word2Vec captures semantic and syntactic relationships between words, allowing for meaningful computations like word analogies.

  9. Kathy Ireland Reveals What She Did to Get Fired from “Saved ...

    www.aol.com/kathy-ireland-reveals-she-did...

    Related: Kathy Ireland Reflects on Her Iconic Modeling Career and the 'Gift' She Received Along the Way (Exclusive) "One example was skincare," she said. "I worked with scientists and was trying ...